Modeling for Inter-Basin Groundwater Transfer Identification between Middle Abay River Basin and Upper Awash River Basin
By:
Dure Mulatu
Addis Ababa University
Addis Ababa, Ethiopia
June, 2017
Addis Ababa University
Addis Ababa Institute of Technology
School of Graduate Studies
School of Civil and Environmental Engineering
Modeling for Inter-Basin Groundwater Transfer Identification between Middle Abay River Basin and Upper Awash River Basin
By: Dure Mulatu
A thesis submitted to the School of Graduate Studies of Addis Ababa University in Partial fulfillment of the Degree of Master of Science in Hydraulic Engineering.
Advisor: Dr - Ing Mebruk Mohammed
June, 2017 Addis Ababa University
Addis Ababa Institute of Technology
School of Graduate Studies
School of Civil and Environmental Engineering
Modeling for Inter-Basin Groundwater Transfer Identification between Middle Abay River Basin and Upper Awash River Basin
A thesis submitted to the School of Graduate Studies of Addis Ababa University in Partial fulfillment of the Degree of Master of Science in Hydraulic Engineering.
By: Dure Mulatu
Approval by Board of Examiners
Dr. Ing Mebruk Mohammed ------Advisor Signature
Dr. Agizew Nigussie ------Internal Examiner Signature
Dr. Belete Birhanu ------External Examiner Signature
Dedication
To my mother Kibe Balcha whom I love very much
Abstract Groundwater flow models are important for the identification of inter-basin groundwater transfer between adjacent basins. Numerical groundwater model, TAGSAC has been used to study the inter-basin groundwater transfer (IBGWT) between middle Abay River basin and upper Awash River basin. Three steady state groundwater flow models (for middle Abay River basin, upper Awash River basin and for the two combined basins) were first created and calibrated for the inventoried wells. The first two models were created by considering the surface water divide between the two basins as a no flow boundary. The third model avoids the surface water divide which justifies IBGWT. The calibration target for this study was the hydraulic head; hydraulic conductivity and surface recharge were used as calibration parameters. The goodness of fit indicators (GoFIs) that was obtained for the third model was better than the other two models. This indicates the evidence of IBGWT between the two basins; i.e. groundwater flows from middle Abay River basin to Upper Awash River basin and from Upper Awash River basin to middle Abay River basin. In addition, the groundwater head distribution for third model showed that the groundwater divide and surface water divide were not coincident. And groundwater is easily accessed within a shallower depth in the Upper Awash River basin compared to the middle Abay River basin.
Keywords: Inter-Basin Groundwater Transfer, Numerical Groundwater Modeling, TAGSAC, Middle Abay River Basin, Upper Awash River Basin, Ethiopia
Addis Ababa Institute of Technology | I
Acknowledgments First of all, I would like to thank the almighty God for providing His grace, love and support throughout this journey.
I have the greatest appreciation for my advisor, Dr. Ing Mebruk Mohammed, who invested his time, knowledge and energy throughout the study. His guidance, dedication and encouragements throughout the study were amazing.
I am very grateful to the Ethiopian Road Authority (ERA) scholarship for making it possible for me to study in Addis Ababa institute of Technology. I also thank organizations: Water Works Design and Supervision Enterprise and Ministry of Water Resources for providing the required secondary data.
Lastly, I would like to thank my family and friends for their constant support and encouragements.
Addis Ababa Institute of Technology | II
Table of Contents
Abstract ...... I
Acknowledgments...... II
List of Figures ...... V
List of Tables ...... VI
List of Acronyms ...... VII
1 Introduction ...... 1
1.1 Statement of the problem ...... 2
1.2 Objective ...... 2
1.3 Structure of the thesis ...... 3
2 Literature Review ...... 4
2.1 Inter-basin Flow ...... 4
2.2 Previous Studies ...... 4
2.3 Groundwater ...... 7
2.3.1 Groundwater Potential ...... 7
2.3.2 Groundwater Recharge ...... 7
2.3.3 Fractured Media ...... 9
2.3.4 Groundwater Modeling ...... 10
2.3.5 Groundwater Flow Equation ...... 12
2.3.6 Boundary Conditions ...... 15
3 Materials and Methods ...... 18
3.1 Description of the Study Area ...... 18
3.1.1 Location of the Study Area ...... 18
3.1.2 Hydrometeorology ...... 19
3.2 Data processing ...... 19
3.3 Modeling for inter-basin groundwater transfer ...... 19
3.4 Data Collection and Analysis ...... 21
Addis Ababa Institute of Technology | III
3.4.1 Meteorology ...... 22
3.4.2 Topography ...... 26
3.4.3 Well and spring inventory ...... 26
3.4.4 Geology ...... 27
3.5 Conceptual Model ...... 29
3.6 Groundwater Modeling ...... 30
3.6.1 Model selection ...... 30
3.6.2 Discretization ...... 31
3.6.3 Boundary Conditions ...... 32
3.6.4 Recharge Boundary ...... 32
4 Result and Discussions ...... 34
4.1 Model Discretization ...... 34
4.2 Model calibration results ...... 36
4.3 Hydrogeology ...... 43
4.4 Groundwater flow direction ...... 46
4.5 Groundwater Accessibility ...... 50
5 Conclusion and Recommendation ...... 52
5.1 Conclusion ...... 52
5.2 Recommendation ...... 53
6 References ...... 54
APPENDEX: well/spring data used in the numerical model...... 56
Addis Ababa Institute of Technology | IV
List of Figures
Figure 2.1 Model ...... 11 Figure 2.2 Representative elementary volume (REV) ...... 13 Figure 3.1 Study Area Location ...... 18 Figure 3.2 Flow chart for inter basin groundwater transfer identification ...... 21 Figure 3.3 Groundwater modeling flow chart...... 22 Figure 3.4 Thiessen Polygon Constructed for the Study Area...... 25 Figure 3.5 Topographic Map of the study area ...... 26 Figure 3.6 well/ spring location of the Study Area ...... 27 Figure 3.7 Geological Map of the Study Area (source: WWDSE)...... 29 Figure 3.8 Boundary Conditions ...... 30 Figure 4.1 Mesh generated for Model 2...... 34 Figure 4.2 Mesh generated for Model 1...... 35 Figure 4.3 Mesh generated for Model 3...... 36 Figure 4.4 Simulated versus measured head comparison for Model 1 ...... 38 Figure 4.5 Simulated versus measured head comparison for Model 2 ...... 39 Figure 4.6 Simulated versus measured head comparison for Model 3 ...... 39 Figure 4.7 well/ spring along the surface watershed divide ...... 42
Figure 4.8 Hydrogeologic map with horizontal hydraulic conductivity, kx...... 45
Figure 4.9 Hydrogeologic map with vertical hydraulic conductivity, kz...... 46 Figure 4.10 Simulated groundwater head and flow direction for Model 3 ...... 48 Figure 4.11 Groundwater divide with surface water divide ...... 48 Figure 4.12 Computed groundwater head and flow directions for Model 2 ...... 49 Figure 4.13 Computed groundwater head and flow directions for Model 1 ...... 50 Figure 4.14 Groundwater Accessibility ...... 51
Addis Ababa Institute of Technology | V
List of Tables Table 3.1 Mean annual rainfall with polygon area ...... 23 Table 3.2 Geologic Characteristics ...... 28 Table 4.1 Summary of calibration errors...... 41 Table 4.2 Summary calibration errors for the wells along the surface watershed divide ...... 41 Table 4.3 Summary of calibration errors (for Well depth ≥ 250m) ...... 42 Table 4.4 Summary of calibration errors (for Well depth < 250m) ...... 43 Table 4.5 Geologic parameters of the study area for classified geological zones...... 44
Addis Ababa Institute of Technology | VI
List of Acronyms BCM: Billion Cubic Meters
DEM: Digital Elevation Model
EPM: Equivalent Porous Medium
FDM: Finite Difference Method
FEM: Finite Element Method
GOFI: Goodness of fit indicator
IBGWT: Inter-basin groundwater transfer m.a.s.l.: meters above sea level
MAE: Mean Absolute Error
ME: Mean Error
Mm3: Million cubic meters
MoWE: Ministry of Water and Energy m/yr: Meter per year
NMSA: National Metrological Service Agency
REV: Representative Elementary Volume
RMSE: Root Mean Square Error
SqKm: Square Kilometer
WWDSE: Water Works Design and Supervision Enterprise
3D: Three dimensional
Addis Ababa Institute of Technology | VII
1 Introduction Groundwater is subsurface water which occurs beneath the earth’s surface. It’s an important earth’s hydrological cycle; groundwater is mostly derived from surface waters (precipitation, lake, reservoir, river, sea, etc.) and percolates into the ground beneath the water table.
Nowadays, groundwater has become a major source of water supply throughout the world. Its use in irrigation, industries, and domestic uses continues to increase. Shortages of groundwater in areas where excessive withdrawals have occurred emphasize the need for accurate estimates of available sub surface resources and the importance of proper planning to ensure the continued availability of water supplies (Todd & Mays, 2005).
Groundwater is a valuable resource due to the storage capacity of groundwater reservoirs and the small flow rates. The increasing groundwater demand for the use of water supply is a major concern for groundwater quality. The major sources and causes of groundwater pollution can be the disposal of wastes on or into the ground from domestic uses, industries, the use of fertilizers pesticides, herbicides on agricultural fields and dissolved carbonate rocks, pyrite, salt…etc. Groundwater pollution is difficult to detect, difficult to control and difficult to be restored to its original state.
Previous studies have shown that Ethiopia has a greater potential of groundwater sources. Therefore, it’s important to study the quantity and quality of this source of water by understanding the hydrological cycle, solute transport within the basins and identify if there is an inter-basin ground water transfer.
Inter-basin groundwater transfer is a process by which groundwater moves from one topographic basin to another through an intervening structural or topographic barrier. It is an important hydrological process that has not been given a special attention among researchers in the study of groundwater hydrology. For a better understanding and management of groundwater flow, the possible occurrence of this hydrological process must be studied.
The possibility of an inter-basin groundwater transfer between the Abay River basin and Awash River basin has been studied by different researchers and governmental offices. These researches used different approaches for the identification of the inter-basin groundwater transfer, but the results were conflicting to one another. The aim of this research is to identify if there is possibility of an inter-basin groundwater transfer between middle Abay River Basin and upper Awash River Basin by using groundwater models.
Addis Ababa Institute of Technology | 1
Groundwater models are used to predict the groundwater flow processes using mathematical equations based on certain simplifying assumptions. Mathematical models can be solved analytically or numerically. Either type of solution may involve computer applications. Ground water models are useful tools to represent or approximate the real system.
1.1 Statement of the problem
The groundwater water flow system and the aquifer system of Abay River basin and Awash River basin have been studied by different researchers for possible inter-basin groundwater transfer (IBGWT). Though these studies use different approaches for the identification the result obtained were conflicting to one another. The potential for groundwater to move from basin to basin is related to the relative altitude and geological structure of the individual basin. Where the rocks that form the boundary between these adjacent basins are sufficiently permeable, there will be flow into or out of the basin. This study will try to work with the premise that IBGWT can at least be detected using head data. Identifying the regional head and checking the geological structure of the two basins can give full information, about the possibility of IBGWT. Thus if the geologic character between the two adjacent basin are similar, then a numerical groundwater model will be developed to show the hydraulic head distribution across the two adjacent basins which ultimately show the possibility of IBGWT.
The aim of this research is to identify if there is a groundwater flow from the middle Abay River basin to upper Awash River basin or not and to identify if there is a possibility of inter- basin groundwater transfer between these two basins by using numerical groundwater models.
1.2 Objective
The main objective of this research is to identify the possibility of inter basin groundwater transfer between middle Abay and upper Awash River basins along their watershed divide through using numerical groundwater modeling.
Specific Objectives
. To draw the groundwater table variation map and flow direction map across the two adjacent basins,
. To redraw/ revise the hydrogeology map,
Addis Ababa Institute of Technology | 2
. To draw the groundwater accessibility map,
1.3 Structure of the thesis
The thesis was organized in six (6) chapters. Chapter 1 provides the general introduction, statement of the problem and objective of the study. Chapter 2 deals with the literature review on inter-basin groundwater flow and groundwater modeling. Chapter 3 states the material and methods used for this thesis, it includes location of the study area, data collection, processing and analysis, groundwater modeling and model conceptualization. Chapter4 is the result and discussion part of the work; it mainly presents the results found from the model calibration. The conclusion and recommendation of this work is stated in Chapter 5. And the lists of the References used for this thesis are presented in Chapter 6.
Addis Ababa Institute of Technology | 3
2 Literature Review
2.1 Inter-basin Flow
Inter basin flow is when a groundwater flows from one basin to another through an intervening structure or topographic barrier (Nelson & L.Mayo, 2004). It is not uniform between all basins but it is common and is a function of the hydraulic gradient between basins and hydraulic conductivity of the intervening rocks. The study of Inter-basin groundwater flow transfer has been recognized by scientific studies over the past century (Belcher, et al. 2009).
Water budget imbalances, Chemical evidence and groundwater head data could be used to study the evidences of inter basin flow between basins. Water budget principle can quantify if there is a gain or loss in watershed that is studied. But usually requires careful measurements of stream discharge and evapotranspiration unless the inter-basin transfer is large enough to be obvious from even approximate estimates of the other fluxes. However, water budgets are too inaccurate to recognize inter-basin transfers. This is because water budget evidences can only show the net gain or loss among basins, not the actual rates of inter-basin seepage and/or out seepage (Genereux, et al., 2001).
Chemical evidence of inter-basin transfer need not take the form of a budget discrepancy; it is often based on observation of stream water that is chemically distinct from water draining hill slopes locally within a watershed. This type of chemical evidence can quantify only a positive inter-basin transfer (gain of groundwater) into the watershed. Water budget and chemical evidences are used to study the possibility of inter-basin groundwater transfer at small watersheds. In a regional scale of identification of inter-basin groundwater transfer groundwater head data is used (Genereux, et al., 2001).
Groundwater head data can show the direction of inter basin transfer through the difference in hydraulic gradient. For an accurate estimation of groundwater flow transfer rate information on hydraulic conductivity and cross-sectional area of the aquifer that is studied should be known (Genereux, et al., 2001).
2.2 Previous Studies
Several researches have been done both by governmental offices and individuals on the study of groundwater flow in Abay and Awash River Basin. But most of the researches did not
Addis Ababa Institute of Technology | 4
include the concept of IBGWT in their studies. Even though the concept of IBGWT has been used in the study of groundwater hydrology in different parts of the world, such a practice is rarely exercised in Ethiopia. But the theory of IBGWT is very important in the study and proper management of groundwater flow. Recent studies by ((Yitbarek, 2009), (WWDSE, 2010), (Azagegn, 2015)and few M.Sc. studies in Addis Ababa University) have applied the theory of IBGWT in their researches.
According to (Yitbarek, 2009) there exists an inter basin groundwater transfer between Abay River Basin and Awash River Basin. By studying the Litho-hydrostratigraphic relationships correlated from the drilling data of the exploratory boreholes coupled with the respective geological structure scenarios and a simple regional steady state numerical groundwater flow model was also used to study the existence of an IBGWT. The numerical groundwater flow model that was developed in this study was for the watershed of the Upper Awash basin by taking into consideration the groundwater inflow from the adjacent Blue Nile basin. A course grid resolution was used (i.e. 2km x 2km) to model the groundwater flow system.
From converging evidences from hydraulic properties of rocks together with hydro chemical data and environmental isotopes supported with simple steady state regional numerical groundwater model (with course grid resolution 2km x 2km) for the Upper Awash groundwater basin (Azagegn, 2015) estimated a total volumetric annual inflow of nearly 590Mm3 into the system of the Upper Awash groundwater basin. Out of the total recharge to the Upper Awash groundwater basin, nearly 26% (153Mm3) is an inflow from the Blue Nile basin through horizontal exchange. The study concluded that evidences from geological studies in agreement with the groundwater level measurements showed that there is an IBGWT from the middle Blue Nile basin to Upper Awash basin. The geological and geophysical investigation of this study showed that a significant portion of the Muger sub basin and small part of Jema sub basin contribute to recharge the volcanic aquifer of the upper Awash Basin. This displays that the surface water and groundwater divides do not coincide at regional scale.
Reports by (WWDSE, 2008) and (WWDSE, 2010) identified that the regional groundwater flow direction extending from Abay Plateau to Awash River Basin. As reported in (WWDSE, 2008) the recharge at Abay plateau flows to Upper Awash Basin through two main directions (through Becho plain and along Legedadi areas) and nearly 100% of Abay plateau is the recharge area of the lower basalt aquifer in Upper Awash basin. The mean annual recharge of
Addis Ababa Institute of Technology | 5
the Ada’a-Becho aquifers system is estimated to be 687 Mm3 with 70% of recharge contributed by Upper Abay River Basin.
From field hydrogeological observation i.e., high yield artesian wells close to water divide of the Awash and Abay basins showed the evidence of inter-basin groundwater transfer from the plateau zone (part of Abay plateau) to the part of the Awash River basin).(Azagegne, 2008)
To investigate the groundwater dynamics between Holeta River catchment from the Upper Awash River basin and tributary streams of Muger River catchment from the Abay River basin; (Hailu, 2016) used an integrated hydro geochemistry and isotope hydrology approach together with water level measurements. And found that the groundwater divide doesn’t coincide with the surface water divide, which is fallen in the Tributary streams of Muger River catchment and there is an inter-basin groundwater transfer between the tributary streams of Muger River catchment and Holeta River catchment.
(Mohammed & Ayalew, 2016) Developed a numerical groundwater model (TAGSAC code); to identify the inter-basin groundwater transfer (IBGWT) between upper Awash River basin and upper rift valley lakes basin of Ethiopia. The results of the research showed that there was an IBGWT between the basins and the surface water divide is not coincident with the groundwater divide.
This research will try to identify if there is possibility of an inter-basin groundwater transfer between middle Abay River Basin and Upper Awash River Basin by using a numerical groundwater model with finer grid resolution (. i.e. 1km x 1km) than the previous studies that was done on these two basins.
The previously done numerical groundwater flow models by (Azagegn, 2015) and (Yitbarek, 2009)only modeled the Upper Awash basin to study the IBGWT between the two adjacent river basins. This was because of the data required for the modeling is more available in the Upper Awash basin than the Middle Blue Nile basin. But this study will try to model the groundwater flow systems of both the Upper Awash and middle Abay River Basins to identify the possibility of IBGWT between the two basins.
Addis Ababa Institute of Technology | 6
2.3 Groundwater
2.3.1 Groundwater Potential
The importance of groundwater resources can hardly be overstated, so it follows that a conceptual understanding of its movement is of great interest and consequence (Mayo, 2014).
The first comprehensive study of the national water resources master plan study attempted to quantify both the surface and sub-surface water resources potential of the country (WAPCOS, 1990) based on basin divisions. As reported by (Belete & Semu, 2013) the total estimated rechargeable groundwater for Awash River Basin varies between 1.3 to 2.2 BCM, while the usable amount is estimated to be in the order of 0.14 BCM. According to (Alemayehu, 2006) the total groundwater reserve of Ethiopia is about 185 BCM; with a mean groundwater recharge of 200 mm for the entire country.
Ethiopia has an abundant surface and groundwater resources potential of which groundwater has a larger share (Energy, 2014).The groundwater potential of Ethiopia is a very controversial topic. It varies from an estimate of around 2.5 BCM to 185 BCM. This extremely high discrepancy in the potential is a challenge to the experts and decision makers (Alemayehu, 2006).
2.3.2 Groundwater Recharge
Precipitation is the principal source for replenishment of moisture in the soil water system to recharge groundwater. The amount of moisture that will eventually reach the water table is going to recharge aquifer system in sub-surface.
Groundwater recharge is important in the proper management of a groundwater basin (USDA, 1967). As the rainfall over Ethiopia is extremely variable in both space and time the recharge to the groundwater system is also variable. The groundwater recharge rate of Ethiopia varies from zero to 250mm/year (Kebede, 2013). Rainfall on the highlands is the main source of recharge for the groundwater system. The major recharge occurs in the northeastern and southwestern plateau where annual rainfall is high. Rapid infiltration occurs in areas which is covered by fractured volcanic and to a lesser extent in sedimentary rocks (Alemayehu, 2006).
According to Ethiopian Geological Survey as reported in (Energy, 2014) the preliminary estimated amount of yearly groundwater recharge of the country is about 28,000 Mm3. But
Addis Ababa Institute of Technology | 7
recent studies indicated that the potential is much greater than this amount. Most of the developed groundwater resource is mainly used for domestic and industrial water supply.
According to Zebene Lakewe (MoWE) studies indicated in (Gebreselassie, 2014) showed that the country’s groundwater is recharged by 36 BCM per year from precipitation and other surface water. Based on the rough assessment of the groundwater potential of the country by (Abebayehu, et al., 2015) reported that the annual groundwater recharge may reach up to 60 BCM; the Abay river basin contributing 19.851 BCM and Awash river basin 3.3996 BCM.
The groundwater recharge variation in middle Blue Nile basin and Upper Awash basin as it has been estimated by (Azagegn, 2015) using Base flow separation method; the groundwater recharge distribution varies from 46mm to 200mm.
The upper Awash River basin above the Becho plain area is assumed to contribute recharge into the upper aquifer of the region. The confined part of the upper Awash plains aquifer (lower basalt aquifer) is mainly recharged over the extended plateau of the Abay basin, above the gorges of Abay River and its tributary rivers. In these areas the lower aquifer is part of the regional groundwater and its main recharge area is situated in Abay Plateau but its discharge area is in Awash River basin (Azagegne, 2008).
The rock units exposed along the Yerer Tulu Wolel Volcanic Lineament zone and the Main Ethiopian Rift margin promote more recharge than the rock units exposed away from these zones. This regional weak zone appears to be the major recharge area. (Azagegne, 2008)
According to the water balance model the mean annual rechargeable water into the upper Awash plains groundwater aquifer systems is more than 965 Mm3, with 67% contributed by Upper Abay basin (Abay Plateau). This result is dependent on the underlying geologic conditions and structural set up which allows deep percolation. Part of the Abay plateau adjacent to the upper Awash is the area that contributes recharge to the groundwater system of the upper Awash besides the recharge with in the Upper Awash (WWDSE, 2008).
The groundwater recharge of the Upper Awash basin was estimated by using the water table fluctuation method. The average aerial annual recharge of the area is estimated to be 85mm, which accounts about 8.7% of the mean annual aerial precipitation of the study area (Yitbarek, 2009).
Addis Ababa Institute of Technology | 8
2.3.3 Fractured Media
A fractured medium consists of solid rock with some primary porosity cut by a system of cracks, micro cracks, joints, fracture zones, and shear zones that create secondary porosity and form a network for flow when interconnected. In order to develop a conceptual model for a fractured system, it either requires a gross simplification or a detailed description of the aquifer properties controlling flow. Information on the primary permeability of the rock matrix and the secondary permeability created by the network of fractures are required to describe a flow through a fractured medium (Anderson & Woessner, 1992).
According to (Cook, 2003) the most common approaches to model fractured systems are: (i) the equivalent porous medium approach, (ii) the discrete fracture approach, and (iii) the dual porosity approach.
2.3.3.1 Equivalent porous medium approach
Fractured material is represented as an equivalent porous medium (EPM) by replacing the primary and secondary porosity and hydraulic conductivity distributions with a continuous porous medium having so called equivalent or effective hydraulic properties. The parameters are selected so that the flow pattern in the EPM is similar to the flow pattern in the fractured system. An EPM approach assumes that the fractured material can be treated as a continuum and that a representative elementary volume (REV) of material characterized by effective hydraulic parameters can be defined. Simulation of flow in fractured systems using this conceptual model requires definition of effective values for hydraulic conductivity, specific storage, and porosity (Anderson & Woessner, 1992).
2.3.3.2 Discrete fracture approach
A discrete fracture model assumes that water moves only through the fracture network. The discrete fracture approach is typically applied to fractured media with low primary permeability such as crystalline rocks. Flow through a single fracture may be idealized as occurring between two parallel plates with a uniform separation equal to the fracture aperture (Anderson & Woessner, 1992).
Addis Ababa Institute of Technology | 9
2.3.3.3 Dual porosity approach
If the rock matrix containing the fracture network has significant primary permeability, a dual porosity model may be used. In this conceptual model, flow through the fractures is accompanied by exchange of water and solute to and from the surrounding porous rock matrix. Obviously, the fracture network as well as the properties of the porous blocks must be described prior to modeling. Aquifer tests may indicate whether a system behaves as a dual porosity system and results can be interpreted to estimate hydraulic conductivities (Anderson & Woessner, 1992).
2.3.4 Groundwater Modeling
A model is the simplified version of a real system and phenomena that take place within it, which represent or approximately simulates the real system (Bear & Cheng, 2010). Groundwater models are used to analyze flow situations in order to understand the flow system (Anderson & Woessner, 1992). Groundwater models can be classified as steady state or transient; confined, unconfined or combination of confined and unconfined; one dimensional, two dimensional, quasi three dimensional, or three dimensional (Todd & Mays, 2005).
But groundwater models are not alternative method for field investigation but it’s a valuable tool used to predict the groundwater flow processes using mathematical equations based on certain simplifying assumptions. This mathematical model can be solved either by using analytical method or numerical method. Either type of solution may involve computer applications.
Recently, computer aided numerical solutions are the major tool for solving problems in practice. The rapid progress in computer technologies has made computers faster, with larger storage capacities, with parallel computing capabilities, etc. It is possible to solve larger and more complex problems faster, cheaper, and more accurately (Bear & Cheng, 2010).
Addis Ababa Institute of Technology | 10
Model
Physical Mathematical Model Model
Analytical Numerical Method Method
Figure 2.1 Model 2.3.4.1 Analytical Method and Numerical Method
Analytical methods simplify groundwater flow equation by assuming homogenous porous medium and one or two-dimensional flow. Except for the applications to well hydraulics, analytical methods are not widely used in practical applications. Numerical methods are much more versatile and, with the widespread availability of computers, are now easier to use than some of the more complex analytical solutions.If groundwater problems become more complex (variation in hydrogeologic paramters), the system becomes too complicated for solutions obtainedwith analytical methods. In these cases, numerical methods have to be used. The introduction of computer programs increased the application of numerical methods and these methodsreplaced almost completely the use of analytical methods in groundwater modelling(Fetter, 2001).The numerical methods that are widely used in groundwater modeling are finite difference method and finite element method.
2.3.4.1.1 Finite Difference Method
Finite difference method widely used and accepted by many governing bodies. It is the most popular groundwater simulator available. The finite difference method is easy to understand, calculate and fewer input data are needed, the solutions are mass-conservative. However, the finite difference method is not without weakness. Although grids are easy to create, they cannot be efficiently refined around areas of interest, such as wells and model boundaries. And also Finite difference grids are rectangular and the area modeled is not. Special problems like
Addis Ababa Institute of Technology | 11
movement of water table and seepage face are difficult to handle (Anderson & Woessner, 1992).
The grid is created using structured, rectilinear (rectangular) grids. Compute a value of the head at the node which also is the average head for the cell that surrounds the node. The node represents the finite difference cell.
2.3.4.1.2 Finite Element Method
The finite element method can also be used to solve the groundwater flow equation. Finite elements are easier to adjust the size of individual’s elements as well as the location of the boundaries with the finite element method. This method is better to handle internal boundaries such as fault zones and water tables.
Finite element methods are able to approximate irregular shaped than the finite difference method. It uses triangular mesh to represent the model domain. The use of triangles allows for a more efficient refinement around wells and boundaries. The triangular mesh can more easily adapt to variable stratigraphy such as sloping or pinch outs, and allows for versatile discretization of non-rectangular model domains. And it allows more flexibility in designing a grid.
Finite element model defines the variation of head within an element by means of interpolation, heads are calculated at the nodes for convenience, but head is defined everywhere by means of basis functions.
Finite element models simulate point sinks and sources more accurately than finite difference model and no correction is needed (Anderson & Woessner, 1992). A disadvantage of finite element models is that the input of data required to define the grid is more laborious than for finite difference models. Finite element models require that each node and element be numbered. The finite element method treats each element separately and then assembles equations for all elements into a global matrix equation.
2.3.5 Groundwater Flow Equation
Before deriving a governing equation for groundwater flow, a conceptual model of the system is needed. There are two conceptual views of gorund water system, the aquifer view point and the flow system view point. Aquifer view point is based on the concept of confined and
Addis Ababa Institute of Technology | 12
unconfined aquifers. It is suited for analysis of flow to pumping wells and is the basis for Theim, Theis and Jacob.Ground water flow is strictly horizontal through the aquifers and srticly vertical through confining beds.Flow system view point allows for both vertical and horizontal flow in two dimensional and three dimensional profile(Anderson & Woessner, 1992).
The governing equation is derived by mathematically combining a water balance equationwith Darcy's law.The derivation is done by referring to a cube ofporous material that is large enough to be representative of the properties of the porous medium and yet is small enough so that the change of head within the volume is relatively small. This cube of porous material is known as a representative elementary volume or REV. Its volume is equal to ΔxΔyΔz Figure 2.2(Anderson & Woessner, 1992).
Figure 2.2 Representative elementary volume (REV) The flow of water through the REV is expressed in terms of the discharge rate (q),whose magnitude in the three coordinates will be qx, qy, and qz
풒 = 풒풙풊풙 + 풒풚풊풚 + 풒풛풊풛 (2.1)
Where ix, iy, iz are unit vectors along the x, y, and z axes.
The water balance equation (or conservation of mass) states that:
표푢푡푓푙표푤 − 𝑖푛푓푙표푤 = 푐ℎ푎푛푔푒 𝑖푛 푠푡표푟푎푔푒 (2.2)
Consider flow along the y axis of the REV in Figure 2.2. Influx to the REV occurs through the face ΔxΔz and is equal to (qy)IN. Flux out is equal to (qy)OUT. The volumetric outflow rate minus volumetric inflow rate along the y axis is:
Addis Ababa Institute of Technology | 13
[(푞 ) − (푞 ) ]∆푥∆푧 (2.3) 푦 푂푈푇 푦 퐼푁
It can also be written as:
(푞푦) −(푞푦) 푂푈푇 퐼푁 (∆푥∆푦∆푧) (2.4) ∆푦
And dropping the IN and OUT subscripts, the change in flow rate through the REV along the y axis is:
휕푞 푦 (∆푥∆푦∆푧) (2.5) 휕푦
Similar expressions can be written for the change in flow rate along the x and z axes. The total change in flow rate is equal to the change in storage and is expressed as:
휕푞 휕푞 휕푞 ( 푥 + 푦 + 푧) ∆푥∆푦∆푧 = 푅푎푡푒 표푓푐ℎ푎푛푔푒 𝑖푛 푠푡표푟푎푔푒 (2.6) 휕푥 휕푦 휕푧
The existence of sink (e.g. a pumping well) or source of water (e.g. injection well or some other source of recharge) within the REV is undeniable. The volumetric inflow rate of such sources is represented by R*∆x∆y∆z. Here the R*is defined to be intrinsically positive when it is a source of water; therefore, it is added to the right-hand side of Eq. (2.6).
휕푞 휕푞 휕푞 ( 푥 + 푦 + 푧 − 푅∗) ∆푥∆푦∆푧 = 푅푎푡푒 표푓 푐ℎ푎푛푔푒 𝑖푛 푠푡표푟푎푔푒 (2.7) 휕푥 휕푦 휕푧
The change in storage is represented by specific storage (Ss). It is defined as the volume of water released from storage per unit change in head (h) per unit volume of aquifer (Anderson & Woessner, 1992)i.e.
∆푣 푠푠 = − (2.8) ∆ℎ∆푥∆푦∆푧
The sign convention is that the ∆V is intrinsically positive when the ∆h is negative, or in other words, water is released from the REV when head decreases. The rate of change in storage in REV will be:
Δv Δℎ = −푠 ∆ ∆ ∆ (2.9) Δ푡 푠 Δ푡 푥 푦 푧
Combining Eq. (2.7) and Eq. (2.9):
휕푞 휕푞 휕푞 휕ℎ 푥 + 푦 + 푧 = −푠 + 푅∗ (2.10) 휕푥 휕푦 휕푧 푠 휕푡
Addis Ababa Institute of Technology | 14
Darcy law is used to set the relationship between q and h. Darcy law in three dimensions is written as (Anderson and Woessner, 1992):
휕ℎ 휕ℎ 휕ℎ 푞 = −퐾 푞 = −퐾 푞 = −퐾 (2.11) 푥 푥 휕푥 푦 푦 휕푦 푧 푧 휕푧 Substituting these expressions in Eq. (2.10) the desired groundwater flow equation is formulated:
휕 휕ℎ 휕 휕ℎ 휕 휕ℎ 휕ℎ (퐾 ) + (퐾 ) + (퐾 ) = 푠 + 푅∗ (2.12) 휕푥 푥 휕푥 휕푦 푦 휕푦 휕푧 푧 휕푧 푠 휕푡
Where Kx, Ky, and Kz are components of the hydraulic conductivity.
In the above derivation it is assumed that Kx, Ky, and Kz are collinear to the x, y and z axes. If the geology is such that it is not possible to align the principal direction of the hydraulic conductivity tensor with the rectilinear coordinate system, a modified form of equation that utilizes the hydraulic conductivity tensor is required.
퐾푥푥 퐾푥푦 퐾푥푧 퐾 = [퐾푦푥 퐾푦푦 퐾푦푧] (2.13) 퐾푧푥 퐾푧푦 퐾푧푧
By using a global coordinate system for the entire problem domain and a local coordinate system for each REV in the grid, the off-diagonal terms in the hydraulic conductivity tensor could have zero value (Anderson & Woessner, 1992).
퐾푥 0 0 퐾 = [ 0 퐾푦 0 ] (2.14) 0 0 퐾푧
2.3.6 Boundary Conditions
Computer simulations of groundwater flow systems numerically evaluate the mathematical equation governing the flow of fluids through porous media. This equation is a second order partial differential equation with head as the dependent variable. In order to determine a unique solution of such a mathematical problem, it is necessary to specify boundary conditions around the flow domain for head (the dependent variable) or its derivatives. These mathematical problems are referred to as boundary value problems. Thus, a requirement for the solution of the mathematical equation that describes groundwater flow is that boundary conditions must
Addis Ababa Institute of Technology | 15
be prescribed over the boundary of the domain. Boundary conditions also represent any flows that are hydrologic boundaries can be mathematically represented in more than one way. The determination of an appropriate mathematical representation of a boundary condition is dependent upon the objectives of the study.
In the groundwater flow modeling process, boundary conditions have an important influence on the areal extent of the model. Ideally in developing a conceptual model, the extent of the model is expanded outward from or head constraints within the flow domain. The selection of the boundary condition is critical to the development of an accurate model. Not only is the location of the boundaries important, but also their numerical or mathematical representation in the model. This is because many physical features the area of concern both vertically and horizontally so that the physical extent coincides with physical features of the groundwater system that can be represented as boundaries. The effect of these boundaries on heads and flows must then be conceptualized, and the best or most appropriate mathematical representation of this effect is selected for use in the model.
The hydrogeologic boundaries are represented by the following three types of mathematical conditions (Uhegbu & Igboekwe, 2011).
1. Constant Head Boundary: This is a type of specified head boundary condition, in which the head is known and the source of water has a constant water level at the model boundary. This condition is used in modeling an aquifer that is in good interaction with a lake, river or another external aquifer. These are usually where the groundwater is in direct contact with surface water such as a lake or a river and drains interact freely with the aquifer. It is mathematically known as Dirichlet boundary. 2. Constant Flux Boundary: This is a type of specified flux boundary condition also known as the second type of boundary condition, and mathematically known as Neumann’s condition or recharge boundaries. Entering or leaving the aquifer is prescribed/constant flux. This boundary condition is used in simulating rainfall or distributed discharge for instance evaporation and also used in specifying known recharge to the aquifer owing to induced recharge 3. No flow Boundary (across which minimal flow occurs): This is a very special type of the prescribed flux boundary and is referred to as no-flux, zero flux, impermeable, reflective or barrier boundary. No flow boundaries are impermeable boundaries that allow zero flux. They are physical or hydrological barriers which inhibit the inflow or
Addis Ababa Institute of Technology | 16
outflow of water in the model domain. No flow boundaries are specified either when defining the boundary of the model grid or by setting grid blocks as inactive (i.e. hydraulic conductivity = 0).
Addis Ababa Institute of Technology | 17
3 Materials and Methods
3.1 Description of the Study Area
3.1.1 Location of the Study Area
The study area is located in the central part of Ethiopia. The capital city, Addis Ababa, is located at the Southeastern part of the study area. The location of study area is 80 39’ 2.13’’N to 100 11’ 2.55’’ N Latitude and 370 37’ 9.47’’ E to 390 2’ 56.92’’ E Longitude. The total area is 17,352 SqKm out of which 82.7% (14,350 SqKm) and 17.3 % (3,002SqKm) is in part of the middle Abay River Basin and Upper Awash River Basin respectively.
Figure 3.1 Study Area Location Boundary conditions are uncertain, particularly if the model boundaries do not correspond to the natural physical boundaries of the aquifer. The study area is selected in a way that it can be bounded by natural physical boundaries in order to avoid boundary condition uncertainties.
The study area is bounded by Guder River in the northeastern direction, Jema River in the northwestern direction; middle Abay River in the northern direction and upper Awash River in
Addis Ababa Institute of Technology | 18
southeastern direction. Guder, Muger and Jema Rivers flow nearly parallel and join the Abay River.
3.1.2 Hydrometeorology
The study area is characterized by varying climatic zones ranging from hot and humid lowlands to cold and dry highlands. The average annual precipitation of the area varies between 800mm and 1200mm. The mean monthly temperature varies between 2.1oc and 31.1oc (Azagegn, 2015).
3.2 Data processing
The first step in groundwater modeling is planning, which is to determine the purpose of the model. The purpose will determine which method shall be used to model the groundwater flow system. Models are designed to answer specific questions; the main objective of this study is to answer if there is an inter basin groundwater transfer between the two adjacent river basins. The second step is to develop a conceptual model of the system using all available field data. This includes information about the boundary conditions, the hydrogeological and the hydrological conditions of the system. The conceptual model can be represented either by two dimensions or three-dimensional diagrams. This step also includes data collection, review and analysis; the collected data should be checked to ensure that there are no possible errors. The next step is model design; in this step the previously developed conceptual model is put into the form that is suitable for modeling. In other words, it is to convert the conceptual model into a mathematical model. The last step is calibration and sensitivity analysis. In this step the accuracy of the model is checked by how well the model output is able to match with the observed data. This is done by altering the key parameters of the model, and this is usually done by a trial and error method till the observed data matches with the model output. The above modeling protocol is adopted from (Merz, 2013) and (Anderson & Woessner, 1992).
3.3 Modeling for inter-basin groundwater transfer
The methodology adapted to model the inter basin groundwater flow is from (Mohammed & Ayalew, 2016). To analyze the possibility of inter basin groundwater transfer between the two adjacent basins; first three groundwater models are created. The first two models are created by assuming that there is no groundwater flow interaction between the two adjacent basins. The two basins are separated by considering the surface divide as Neumann boundary condition
Addis Ababa Institute of Technology | 19
with zero flux. The third model is created by assuming there is no barrier between the two basins and there is a free movement of groundwater flow between the basins. This is by considering that the watershed divide doesn’t exist for this model.
The three groundwater models are:
Model 1: The groundwater flow model for the middle Abay River basin, it is bounded by middle Abay River, Guder River, Jema River and watershed divide with the Awash River Basin.
Model 2: The groundwater flow model for the Upper Awash River basin, it is bounded by the Upper Awash River and the watershed divide with the middle Abay River Basin.
Model 3: The groundwater flow model for the combination of Upper Awash and middle Abay River basins, it is bounded by Upper Awash River, middle Abay River, Guder River and Jema River
Each of the above three models will be calibrated for all the observed data (well & spring inventory data). This is done by changing the hydrogeological parameters and surface recharge. In order to identify the possibility of inter basin groundwater transfer; the results of the first two models will be compared with the third model which is the combination of the two basins. This is done by taking only the results of the wells/springs that are found in the upper Awash River Basin from the combined model (Model 3) and comparing it with the results of the independent upper Awash model (Model 2). The same procedure is also performed for the other model. The measure of goodness of fit indicator (GoFI) is used for comparison.
Addis Ababa Institute of Technology | 20
Figure 3.2 Flow chart for inter basin groundwater transfer identification
3.4 Data Collection and Analysis
Prior to the groundwater modeling work, existing data were first collected from different offices such as: metrological data, well inventory data, geological map and topographic data. The collected data has been checked for data quality and consistency. Computer software like ArcGIS 10.2.2, Matlab7.11.0 (R2010b) programming language and Surfer 10 were used for data quality checking and analysis.
Addis Ababa Institute of Technology | 21
Figure 3.3 Groundwater modeling flow chart
3.4.1 Meteorology
The meteorological data was collected from the National Meteorological Service Agency (NMSA). Within and nearby the study area 83 metrological stations were found. Among the 83 metrological stations only the 62 metrological stations were found to contribute to the study area. The data collected has been checked for data consistency and accuracy. Thiessen polygon method was adopted to assign the annual rainfall distribution over the study area.
The Thiessen Polygon method is the most common approach used in hydrometeorology to determine the areal rainfall average over an area. This is done by sub dividing the watershed into polygonal subareas using rainfall stations as their centers. These polygonal subareas are
Addis Ababa Institute of Technology | 22
the areas of influence of each rainfall stations. The subareas are used as weights in estimating the watershed average depth(Warren & Gary, 1996).
The weighted average is calculated by:
∑ 푃𝑖퐴𝑖 푃푎푣 = ∑ 퐴𝑖
Where: Pav is the weighted average areal rainfall, Pi is the mean annual rainfalls recorded at each rain gauge stations, Ai area of each polygonal subarea
The weighted average annual rainfall over the study area estimated by Thiessen Polygon method is 1293.85mm. The Thiessen Polygon analysis is shown in Table below.
Table 3.1 Mean annual rainfall with polygon area
Station Name UTM E UTM N Annual Rainfall (mm) Polygon Area (km2) Addis Ababa 475200 1001000 1206.73 588.50 Addis Alem 426600 998000 1175.86 527.60 Akaki Beseka 478300 980100 1060.65 109.00 Alem Gena 463100 989700 1200.70 178.10 Ali Doro 447000 1078000 1388.09 241.90 Ambo 378500 990900 1269.42 529.60 Bete Nigus 371200 1101000 1172.99 199.50 Bicho 389600 1016000 1409.73 343.10 Biriti 417300 1079000 1212.65 405.80 Boneya 462900 972900 1128.90 188.40 Chancho 472800 1022000 1271.56 496.60 Chobi 374700 1031000 1351.00 656.80 Chulute 360000 1064000 1444.23 382.80 Daleti 453800 1063000 1365.78 468.00 Debra 465200 1047000 1195.47 168.60 Debre Genet 423800 973800 1076.99 12.64 Debre Libanos 484900 1074000 1306.79 117.80 Debre Tsige 475700 1067000 1383.94 218.60 Dedu 335600 1070000 1491.60 17.88
Addis Ababa Institute of Technology | 23
Degem 460400 1087000 1434.10 302.00 Dilela 381500 954200 1204.34 9.97 Duber 493300 1045000 1395.47 316.10 Ejere 448200 1104000 1282.98 537.80 Fetire 482900 1107000 1269.79 67.20 Fiche 471500 1085000 1333.10 331.60 Filikilik 422400 1117000 982.88 177.10 Gebre Guracha 435300 1081000 1320.93 263.00 Ginchi 403400 995500 1245.41 629.30 Goja 400200 1024000 1436.51 157.90 Gola 409900 1024000 1361.91 243.90 Gorfo 482000 1037000 1320.68 292.50 Gosha Tsiyon 420500 1106000 1046.85 169.90 Guder 360900 978300 1317.04 50.31 Gundo Meskel 466400 1135000 1265.18 19.59 Holota 447000 1006000 1328.97 617.40 Hose 402200 1097000 1121.39 544.00 Inchini 433900 1026000 1398.02 415.40 Jemo Lefo 392800 1071000 1408.09 785.30 Kachisi 372000 1056000 1394.09 636.30 Kembolcha 410100 1052000 1289.24 297.00 Kere Dobi 360800 1081000 1296.36 364.80 Ketket 412500 1039000 1286.36 184.20 Kewo 334800 1097000 1353.65 6.79 Kombolcha_EW 336100 1047000 1621.30 70.98 Lemen 463600 947300 1103.86 24.00 Lemi 491400 1086000 1378.00 1.54 Mekoda 431000 1051000 1335.76 342.90 Melka Kunture 457300 961700 1012.23 219.10 Minare 421300 1064000 1242.62 328.00 Muger 454900 1049000 1033.79 184.10 Muke Turi 484600 1057000 1412.14 317.90
Addis Ababa Institute of Technology | 24
Mulo 460800 1032000 1278.16 254.00 Rob Geba 355800 1016000 1488.02 270.80 Sebeta 454400 986300 1096.73 157.70 Sendafa 497700 1010000 1188.62 96.82 Shikute 393100 1042000 1343.37 347.40 Shino 420900 1026000 1387.72 235.00 Tefki 443100 977400 1133.43 338.10 Tulu Miki 428700 1098000 1150.10 311.80 Weberi 504900 1065000 1375.36 74.04 Welenkombi 444800 1038000 1372.10 371.20 Wenoda 507900 1033000 1429.22 107.00
Figure 3.4 Thiessen Polygon Constructed for the Study Area
Addis Ababa Institute of Technology | 25
3.4.2 Topography
The topographic data was obtained from the Digital Elevation Model (DEM) of resolution 30m x 30m. The Digital Elevation Model (DEM) data has been modified by using ArcGIS 10.2.2 software. This is done by using the ArcHydro tool (i.e. DEM reconditioning), imposing the stream/ river data which is the linear feature on to the raw DEM. And another ArcHydro tool (i.e. Fill Sinks) were used to modify the elevation by filling the sinks until it drains to the neighboring cell. The top elevations were defined from the modified DEM and the missed elevations were filled by using interpolation. The elevation of the study area varies between 943 m.a.s.l and 3514 m.a.s.l.
Figure 3.5 Topographic Map of the study area 3.4.3 Well and spring inventory
A total of 1234 wells/springs were inventoried within the study area boundary from Water Works Design and Supervision Enterprise (WWDSE) and previously done researches. After
Addis Ababa Institute of Technology | 26
data quality and consistency check only 762 wells/spring holding information on location (UTM coordinate), static water level and well depth were used for this study. From these 653 wells are located in the upper Awash River Basin and 139 wells in the middle Abay River basin. The selection was based on the location and distribution in the area. The maximum well depth and minimum well depth that are available within the study area are 880m and 7m respectively.
Figure 3.6 well/ spring location of the Study Area 3.4.4 Geology
The geologic map of Ethiopia has been done by different offices (Water Works Design and Supervision Enterprise, Ethiopian Mapping Agency and others). For this study the geological map of Ethiopia that was developed by WWDSE was used mainly to know the geologic characteristics of the aquifer within model domain. ArcGIS 10.2.2 was used to delineate the geological map within the study area boundary. The study area is composed of 14 geologic characteristics, as shown in Table 3.2.
Addis Ababa Institute of Technology | 27
Table 3.2 Geologic Characteristics ID Geology ARl Alghe Group: Biotite and hornblende gneisses, granulite and migmatite with minor metasedimentary gneisses
Ja Adigrat formation: Triassic - Middle Jurassic Sandstone
Jb Abay formation: Middle - Jurassic limestone shale and gypsum
Jt Antalo formation: Limestone
Ka Amba Aradom formation: Sandstone, conglomerate and shale
Nc Chilalo formation (lower part): Trachyte, trachy basalt, peralkaline rhyolite with subordinte alkaline basalt
Nn Nazret series- Ignimbrites, unwelded tuffs ash flows, rhyolite flows, domes and trachyte
NQtb Bishoftu formation: Alkaline basalt and tarchyte
Ntb Tarmaber megezez formation: Transitional and alkaline basalt
P2a Ashangi formation: Deeply weathered alkaline and transitional basalt flows with rare interactions of tuff, often tilted (includes Akobo basalts of SW Ethiopia)
P3a Aiba Basalts: food basalts woth rare basic tuff
PNa Tarmaber Gussa formation: Alkaline to transitional basalts often forming shield volcanoes with minor trachyte and phonolite flows
Q aluvial and lacustrine deposits: sand, silt, clay, diatomite, limestone and beach sand
Qb1 Plateau Basalt - Alkaline basalt and trachyte
Addis Ababa Institute of Technology | 28
Figure 3.7 Geological Map of the Study Area (source: WWDSE)
3.5 Conceptual Model
A conceptual model is a descriptive representation of the groundwater flow system to be studied and it incorporates an interpretation of the geological & hydrological conditions. The main purpose of building a conceptual model is to simplify the field problem and organize the associated field data so that the system can be analyzed more readily. The data that are needed to formulate the conceptual model are the hydrogeologic data and topographic data of the groundwater system and these data are also used to check model calibration. The more the conceptual model approximates to the field situations the more accurate is the numerical model (Anderson & Woessner, 1992).
A complete reconstruction of field system is not feasible and partly because there is rarely sufficient data to completely describe the system in full details therefore simplifying assumptions are required. The conceptual model should therefore be kept as simple as possible Addis Ababa Institute of Technology | 29
while retaining sufficient capacity to adequately represent the physical elements of the hydrological behavior (Vijai & Rohit, 2011).
Preparation of conceptual model involves identification of the study area, deciding appropriate boundary conditions (Vijai & Rohit, 2011). A conceptual model was developed for the study area prior to the numerical modeling. In this study, ArcGIS 10.2.2 has been extensively used for the development of the conceptual groundwater flow model for the study area.
Figure 3.8 Boundary Conditions 3.6 Groundwater Modeling
3.6.1 Model selection
Due to the heterogeneities in geologic materials and structural complexities in the Upper Awash River Basin and middle Blue Nile Basin (Azagegn, 2015); a three-dimensional finite element method was chosen to simulate the three-dimensional groundwater flow system.
Addis Ababa Institute of Technology | 30
Finite element method has several advantages over the other numerical methods; irregular or curved aquifer boundaries, anisotropic and heterogeneous aquifer properties, and sloping soil and rock layers can be easily incorporated into the numerical model, the accuracy of solutions to groundwater flow is very good and simulate point sinks and sources more accurately than finite difference method.
The finite element method is implemented with different shapes of elements; triangular elements and trapezoidal elements. Triangular elements are defined by three nodes one at each corner. These nodes serve the purpose of locating unknown heads; that is they are the points within the model domain at which the heads are computed (Herbert & Mary, 1982). For this study triangular elements are selected to develop the finite element mesh.
For this study TAGSAC code was adopted to solve the groundwater flow equation. TAGSAC is a numerical groundwater model which solves a three-dimensional groundwater flow equation in heterogeneous porous media using the Finite element method. Compared to the other groundwater flow models the data requirements of TAGSAC code is minimal.
3.6.2 Discretization
In a numerical groundwater modeling, the continuous groundwater basin will be replaced by a discretized groundwater basin consisting of an array of nodes. The nodal grid forms the framework of the numerical model. The determination of the space between the nodes will depend on the overall size of the modeled area and the computation capacity of the computer. A small number of nodes are preferred in order to minimize data handling, computer storage and computation capacity. But as the number of the nodes increase the level of accuracy will also increase (Anderson & Woessner, 1992).
Addis Ababa Institute of Technology | 31
Due to the size of the model domain and computational capacity of the computer, the element size of the triangular mesh is limited to 1,000m. The elements represent the hydrogeological parameters and nodes represent head. Each node is represented by (X, Y, Z) Cartesian coordinates and is assigned with nodal number. Each of the triangular prisms is described by six nodes.
3.6.3 Boundary Conditions
Boundary conditions are a key component of the conceptualization of a groundwater system. A mathematical model consists of a governing equation, boundary conditions, and initial conditions. Boundary conditions are important to determine the mathematical solutions. The critical step in a numerical model designing is the correct assignment of boundary conditions. Whenever possible it’s preferred to use natural hydrogeologic boundaries as the boundaries of the model (Bear & Cheng, 2010). In steady state simulations, the boundaries largely determine the flow pattern (Anderson & Woessner, 1992).
For the assignment of boundary conditions of the study area, natural boundaries were used as much as possible. A constant head boundary was set to all the rivers only to the location where its perennial (Upper Awash River, middle Abay River, Guder River, Jema River and Muger River) and the two lakes for all the three models (Model 1, Model 2 and Model 3) as shown in Figure 3.8. The watershed divide between the two River basins is treated as a no flow boundary for Model 1 and Model 2.
The top surface elevation was extracted from 30m x 30m resolution DEM and by subtracting the top layer elevation from the aquifer thickness the bottom layer elevation was obtained. An aquifer thickness of 1500m is considered for the 3D groundwater flow models. And it is assumed that there is an impervious layer at 1500mbelow the surface and this serves as the bottom boundary of the model. Since it’s in a very large depth its effect will be minimal. Therefore, the boundary of the bottom surface is taken as no flow boundary conditions. The top surface is assigned to recharge boundary.
3.6.4 Recharge Boundary
Water seeping into an aquifer is known as recharge; Recharge occurs where permeable soil or rock allows water to readily seep into the groundwater. The main source of water entering the model is from the top surface boundary condition, which is the rainfall recharge. Rainfall
Addis Ababa Institute of Technology | 32
recharge to the groundwater depends on surface lithology. And it ranges from 1% to 50%; 40% to 50% rainfall recharges groundwater in high porous medium; 5 to 25 % in moderately porous medium (Raymond, 1992). Since recharge is one of the parameters that is used in the model calibration, during the calibration process the recharge fraction was set to vary from 5% to 25%.
Addis Ababa Institute of Technology | 33
4 Result and Discussions
4.1 Model Discretization
The number of nodes generated for the three groundwater models were 33838, 7434 and 41650 for Model 1, Model 2 and Model 3 respectively. The number of elements generated for the three groundwater models were 33276, 7026 and 40791 for Model 1, Model 2 and Model 3 respectively. Figure 4.1, Figure 4.2 and Figure 4.3 shows mesh generated for Model 2, Model 1 and Model respectively.
Figure 4.1 Mesh generated for Model 2
Addis Ababa Institute of Technology | 34
Figure 4.2 Mesh generated for Model 1
Addis Ababa Institute of Technology | 35
Figure 4.3 Mesh generated for Model 3 4.2 Model calibration results
Calibration refers to a demonstration that the model is capable of producing field measured heads which are the calibration values. Calibration is accomplished by adjusting a set of parameters (recharge rate and hydrogeological parameters) to produce simulated heads that match field measured values (Anderson & Woessner, 1992).This is done by using the trial and error technique. The trial and error technique imply a manual parameter adjustment where
Addis Ababa Institute of Technology | 36
initial parameter values are adjusted in a sequential model run to match simulated heads to observed ones. For this study the trial and error technique is used to calibrate the groundwater flow models. The calibration target for this study is the hydraulic head; hydraulic conductivity and surface recharge were used as calibration parameters. In order to evaluate calibration results it is helpful to know how well the calibrated model matched each of the calibration targets. A flow model is said calibrated, when the simulated head match the observed ones within an acceptable margin of error.
A steady state calibration was done by using the observed heads (static water level) from 762wells/springs. And the effectiveness of the calibration was checked by using the lumped quantitative performance measures. The lumped quantitative performance measures of calibration are used to average error in the calibration. The three ways that are commonly used to express the average difference between simulated and measured heads are:
1. The mean error (ME) is the mean difference between measured heads (hm) and
simulated heads (hs).
푛 1 푀퐸 = ∑(ℎ − ℎ ) 푛 푚 푠 𝑖 𝑖=1
Where n is the number of calibration measurements. Because both positive and negative residuals are used in the calculation, this value should be close to zero for a good calibration.
2. The mean absolute error (MAE) is the mean of the absolute value of the differences in measured and simulated heads.
푛 1 푀퐴퐸 = ∑|ℎ − ℎ | 푛 푚 푠 𝑖 𝑖=1 The MAE measures the average magnitude of the errors in a set of predictions, without considering their direction.
3. The root mean squared error (RMSE) or the standard deviation is the average of the squared differences in measured and simulated heads.
Addis Ababa Institute of Technology | 37
푛 1 푅푀푆퐸 = √ ∑(ℎ − ℎ )2 푛 푚 푠 𝑖 𝑖=1
The RMSE is used as the basic measure of calibration for heads.
Scatter plots are used to assess the quality of calibration simulations. Observed head versus the head computed by the model are plotted. In an ideal calibration, the points will fall on a straight line with a 45-degree slope; which means the computed head equals the observed head. The degree of scatter about this theoretical line is a measure of overall calibration quality(Anderson & Woessner, 1992).In this study, the coefficient of determination (R2) between the observed and simulated values was found to be 0.918, 0.696 and 0.796 for Model 1, Model 2 and Model 3 respectively. This values of the correlation coefficient (R2) being closer to 1 indicates a good performance of the models (Model 1 and Model 3).
4000
3500 y = x
3000
2500 y = 0.981x R² = 0.918
2000 SimulatedHead
1500
1000 1000 1500 2000 2500 3000 3500 4000 Measured Head
Figure 4.4 Simulated versus measured head comparison for Model 1
Addis Ababa Institute of Technology | 38
3400 y = x 3200 3000 2800
2600 y = 0.9928x R² = 0.696
2400 SimulatedHead 2200 2000 1800 1800 2000 2200 2400 2600 2800 3000 3200 3400 Measured Head
Figure 4.5 Simulated versus measured head comparison for Model 2
4000
3500 y = x
3000
2500 y = 1.0023x R² = 0.7961
2000 SimulatedHead
1500
1000 1000 1500 2000 2500 3000 3500 4000 Measured Head
Figure 4.6 Simulated versus measured head comparison for Model 3
Head measurements could be subjected to measurement error associated with the accuracy of the water level measuring device, the operator, and the location and accuracy of the elevation survey point. And another source of error is caused by scaling effects. The maximum acceptable value of calibration criterion depends on the magnitude of the change in head over the problem domain. As a general calibration criteria RMSE equal to or less than 10% of the observed head range in the aquifer being simulated is better (Anderson & Woessner, 1992). The observed head range value for Model 1 is from 1213.88m to 3041.76m, Model 2 is from
Addis Ababa Institute of Technology | 39
1934.60m to 2978.97m and Model 3 is from 1209.93m to 3043.3478m.As it shown in Table 4.1 the RMSE value for all the models (Model 1, Model 2 and Model3) is less than 10 %of the observed head range in each model, which indicate that the models were well calibrated.
From Table 4.1 it is evident that Model 3 for the whole wells represents a better result than that of the other models. This clearly shows that the evidence of the influence of the two basins on each other and the no flow boundary that was set between the Abay basin and the Awash basin for both models, Model 1 and Model 2 doesn’t help in improving the model accuracy. Model 1 represents a better result than the result of Model 3 for the wells observed in the Abay basin. From this result it can be observed that Abay basin is slightly influenced by the Awash basin. But the Awash basin is highly influenced by the Abay basin.
Both (Yitbarek, 2009) and (Azagegn, 2015) tried to model the groundwater flow system of Upper Awash aquifer system to study the inter basin groundwater transfer between Abay River basin and Awash River basin using a finite difference method approach with 2km x 2km grid size. A root mean squared error of 6% was achieved at the end of the calibration for the observed head range in Upper Awash aquifer by (Yitbarek, 2009) and RMSE of 39m was achieved by (Azagegn, 2015).
This study tried to model the groundwater flow system of both the middle Abay River basin and the upper Awash River basin, by using a finite element method approach with 1km x 1km grid size and a RMSE of 4.465% was achieved at the end of the calibration. As compared with previously done researches, these findings are better because of the finer grid size used and also the study tried to model both basins to study their inter basin groundwater transfer. But to study IBGWT between two basins the water budget imbalances and Chemical evidence have to be studied in addition to the groundwater modeling.
The results from the wells along the surface watershed divide including the wells in Addis Ababa city and its surroundings shown in Table 4.2 indicates the evidence of inter basin groundwater transfer between the two adjacent basins i.e. middle Abay River basin and upper Awash River basin. Model 3 represents better the wells observed in upper Awash River basin than Model 2. This clearly shows that the influence of the neighbor middle Abay River basin on upper Awash River basin; in Model 2 this influence was blocked by the no flow boundary assumed. The presence of the no flow boundary between the middle Abay River basin and upper Awash River basin in Model 2 doesn’t help in improving the model accuracy for the wells along the surface watershed divide.
Addis Ababa Institute of Technology | 40
Table 4.1 Summary of calibration errors.
Models ME MAE RMSE RMSE % R2
Model 1 (middle Abay) 46.835 60.054 94.361 5.144 0.918
Model 2 (upper Awash) 12.799 46.297 68.561 6.560 0.696
Model 3 for whole wells 9.349 59.910 81.860 4.465 0.796
Model 3 for wells in Model 1 76.990 87.800 120.675 6.558 0.894
Model 3 for wells in Model 2 -28.504 53.722 70.405 6.677 0.772
Table 4.2 Summary calibration errors for the wells along the surface watershed divide
Models` ME MAE RMSE Intercept R2
Model 1 (middle Abay) -1.896 34.722 47.230 1.001 0.914
Model 2 (upper Awash) 31.930 53.978 77.080 0.985 0.063
Model 3 for whole wells -14.507 57.323 70.700 1.005 0.203
Model 3 for wells in Model 1 55.428 77.625 96.230 0.977 0.597
Model 3 for wells in Model 2 -20.276 55.648 67.998 1.007 0.163
Addis Ababa Institute of Technology | 41
Figure 4.7 well/ spring along the surface watershed divide
Table 4.3 Summary of calibration errors (for Well depth ≥ 250m)
Models ME MAE RMSE Intercept R2
Model 1 (middle Abay) -23.159 23.923 32.149 1.009 0.830
Model 2 (upper Awash) 2.123 41.958 57.810 0.997 0.839
Model 3 for whole wells -33.090 61.269 80.941 1.013 0.800
Model 3 for wells in Model 1 -23.159 23.923 30.780 1.009 0.829
Model 3 for wells in Model 2 2.123 41.958 57.810 0.997 0.839
Addis Ababa Institute of Technology | 42
Table 4.4 Summary of calibration errors (for Well depth < 250m)
Models ME MAE RMSE Intercept R2
Model 1 (middle Abay) 52.897 63.183 97.907 0.979 0.923
Model 2 (upper Awash) 14.942 47.168 70.522 0.992 0.641
Model 3 for whole wells 2.991 58.881 82.732 0.997 0.789
Model 3 for wells in Model 1 52.897 63.183 97.907 0.979 0.923
Model 3 for wells in Model 2 14.942 47.168 70.522 0.992 0.641
The results of the models for well depth greater than 250m and for well depth less than 250m has been compared to see the performance of the models based on the well depth. As it can be seen from Table 4.3 and Table 4.4 the models represent good results for the well depth ≥ 250m than that of the well depth < 250m. This is because the model is regional groundwater flow model and it simulates better for the deep wells which are influenced by the regional groundwater flow systems than the shallow wells.
4.3 Hydrogeology
The hydraulic head is computed for the three models by varying the hydraulic conductivity for the ten geologic zones of the area and the surface recharge. The study area is classified into fourteen geological zones but only ten of them are taken as hydrogeologic calibration parameters of the area. This is because of their small size relative to the other ten geologic zones and also their location in the model basin. By using the trial and error process for the model calibration, the parameters in Table 4.5 are selected as the best from the other combinations. The hydrogeologic map of the study area was drawn by using the results from the calibrated model. The hydrogeolgic map of the study area is shown in Figure 4.8 and Figure 4.9. The results of the horizontal and the vertical hydraulic conductivity showed that the horizontal hydraulic conductivity is more dominant than the vertical hydraulic conductivity. Higher hydraulic conductivity values indicate that groundwater flows faster in that region and lower hydraulic conductivity values indicate groundwater flows slower in that regions. The results of the horizontal and the vertical hydraulic conductivity classified as low, medium and
Addis Ababa Institute of Technology | 43
high respective to the study area hydraulic conductivity values are shown in Figure 4.8 and Figure 4.9 respectively.
Table 4.5 Geologic parameters of the study area for classified geological zones.
Model Basins Geology no. Kx(m/yr) Ky(m/yr) Kz(m/yr) Recharge Model 1 (middle 2 4.32E-01 4.32E-01 4.32E-02 15% Abay River Basin) 3 6.91E-01 4.32E-01 6.91E-02 4 6.05E-01 4.32E-01 6.05E-02 6 8.64E-01 1.73E-01 8.64E-02 7 5.18E-01 8.64E-02 5.18E-02 9 8.64E-01 5.18E-01 8.64E-02 10 3.46E-01 8.64E-02 3.46E-02 11 4.32E-01 1.73E-01 4.32E-02 12 2.28E-02 2.28E-02 2.28E-03 Model 2 (upper 7 3.46E-01 8.64E-02 3.46E-02 10% Awash River Basin) 9 4.32E-01 2.59E-01 4.32E-02 12 1.47E+00 6.91E-01 1.47E-01 13 1.73E+00 4.32E-01 1.73E-01 Model 3 (middle 2 8.64E-01 6.91E-01 8.64E-02 10% Abay River Basin 3 6.91E-01 6.05E-01 6.91E-02 and upper Awash 4 8.64E-01 7.78E-01 8.64E-02 River Basin) 7 4.32E-01 3.46E-01 4.32E-02 9 1.73E+00 1.56E+00 1.73E-01 10 8.64E-01 7.78E-01 8.64E-02 11 8.64E-01 7.78E-01 8.64E-02 12 6.05E-01 5.18E-01 6.05E-02 13 1.73E+00 1.64E+00 1.73E-01 14 5.18E-01 4.32E-01 5.18E-02
Addis Ababa Institute of Technology | 44
Figure 4.8 Hydrogeologic map with horizontal hydraulic conductivity, kx.
Addis Ababa Institute of Technology | 45
Figure 4.9 Hydrogeologic map with vertical hydraulic conductivity, kz.
4.4 Groundwater flow direction
Generally, groundwater flows from a higher head to a lower head. By using the hydraulic heads from the calibrated model, groundwater flow directions with groundwater level contour map were plotted for all the three groundwater models as shown in the figure below. Narrow contour spacing corresponding to high hydraulic gradients indicates rapid change in elevations of water level compared with those of wider spacing contours. As it is seen from the groundwater level contour map, groundwater flows following the general surface topography and finally converges into the respective river flow directions. The groundwater level in the study area ranges from 900m to 3150m. The groundwater flow direction array shows the magnitude and the direction of flows. The length of the arrow indicates the magnitude of the flow, in which the longer arrow the higher the magnitude. Which means arrow with higher magnitude shows that the groundwater flows faster in that area and slower for arrows with lower magnitude.
Addis Ababa Institute of Technology | 46
From the groundwater flow direction map of Model 1 shown in Figure 4.13, majority of the flow direction arrow indicates that groundwater flows away from the watershed divide and flows in to their respective rivers (i.e. Guder River, Muger River, Jema River and middle Abay River). And the groundwater flow direction map for Model 2 in Figure 4.12 also showed that groundwater flows away from the watershed divide into the Upper Awash River and into its tributaries. This is because of the no flow boundary that was set along the watershed divide for both Models.
The groundwater flow direction map and the groundwater level contour map for Model 3 showed that there is an inter basin groundwater transfer between the middle Abay River basin and upper Awash River basin. As it is shown in the Figure 4.10, majority of the groundwater flow direction around the watershed divide moves from the middle Abay River Basin to the upper Awash River Basin.
In Figure 4.11 the groundwater divide and surface divide is shown. It indicates that the groundwater divide doesn’t coincide with the surface water divide. And it also indicates that there is an evidence of inter basin groundwater transfer between the middle Abay River basin and upper Awash River basin. In regions AB, CD, EF, GH, JK groundwater is flowing from the upper Awash River basin to the middle Abay Basin and in regions BC, DE, FG, HI groundwater is flowing from middle Abay River basin to upper Awash River basin
Addis Ababa Institute of Technology | 47
Figure 4.10 Simulated groundwater head and flow direction for Model 3
Figure 4.11 Groundwater divide with surface water divide
Addis Ababa Institute of Technology | 48
Figure 4.12 Computed groundwater head and flow directions for Model 2
Addis Ababa Institute of Technology | 49
Figure 4.13 Computed groundwater head and flow directions for Model 1
4.5 Groundwater Accessibility
By using the results of the hydraulic head from the calibrated model, the groundwater accessibility map was drawn as shown in Figure 4.14. The groundwater accessibility map of the study area shows that the groundwater accessibility depth varies from 0 m to 1050m below the surface ground level. Shallow groundwater level is dominant over the study area which can be easily accessed 150m below the surface ground level. Majority of the areas within the upper Awash River Basin of the study area, groundwater can be accessed within a shallower depth i.e. 150m below surface ground level. This shows that groundwater is easily accessed in this Basin compared to the middle Abay River basin which shows a significant amount of
Addis Ababa Institute of Technology | 50
variation of groundwater accessibility depth within a shorter distance. This is because of the surface topography of the basin which varies abruptly.
Figure 4.14 Groundwater Accessibility
Addis Ababa Institute of Technology | 51
5 Conclusion and Recommendation
5.1 Conclusion
To study the evidences of inter basin groundwater flow between basins, Water budget imbalances, Chemical evidence and groundwater head data could be used. Among this groundwater head data was used for this study, which was done by making use of groundwater flow system modeling. Groundwater head data can show the direction of inter basin transfer through the difference in hydraulic gradient. But water budget imbalances and chemical evidence should also be used together with groundwater head data for an accurate result.
To identify the IBGWT three groundwater models were created first (Model 1 for middle Abay River basin, Model 2 for upper Awash River basin and Model 3 for combined middle Abay River basin and upper Awash River basin). The first two models (Model 1 and Model 2) were created by assuming that there is no groundwater flow interaction between the two adjacent basins. The two basins are separated by considering the surface water divide as a no flow boundary. The third model (Model 3) was created by avoiding the surface water divide between the two basins and treating the two basins as one. The calibration of these three models was made by changing the recharge and hydrogeologic parameters of the basins.
A total of 762 well/ springs (139 for Model 1, 623 for Model 2 and 762 for Model 3) were inventoried for the model calibration. The simulated and measured hydraulic head at these well/spring locations is tested for measure of goodness of fit. The goodness of fit indicator, RMSE obtained for the Model 1, Model 2 and Model 3 were 5.144%, 6.560% and 4.465% respectively. All the results are below the recommended value for calibrated model. The result obtained from Model 3 clearly indicates that there is an evidence of IBGWT between middle Abay River basin and upper Awash River basin. And it also showed that the assumption that the groundwater divide and surface water divide are coincident is not valid for this case.
Groundwater can be accessed within a shallower depth i.e. 150m below surface ground level, in majority of the areas within the upper Awash River Basin of the study area. This shows that groundwater is easily accessed in this Basin compared to the middle Abay river basin which shows a significant amount of variation of groundwater accessibility depth within a shorter distance.
Addis Ababa Institute of Technology | 52
In general, this study has provided that there is an evidence of IBGWT between the two basins (middle Abay and upper Awash River basins). And the surface water divide and groundwater divide are not coincident. These results are useful to study the cross contamination of the groundwater flow system.
5.2 Recommendation
. As the size of the grid decrease the level of the model result accuracy will increase; which means the finer the groundwater model grid, the more accurate will the results be. So, if finer grid spacing is used the level of the model accuracy will increase and the model can better simulate the real groundwater flow system.
. Transient groundwater modeling can better simulate the actual groundwater flow system than a steady state groundwater modeling. But due to lack of data a steady state groundwater modeling was used in this study.
. For a better identification of the IBGWT between two basins the Water budget imbalances and Chemical evidence have to be studied in addition to the groundwater flow modeling.
. The result of this study indicated that there is an evidence of inter basin groundwater transfer between the middle Abay River basin and upper Awash River basin; i.e. groundwater flows from middle Abay river basin to upper Awash river basin and from upper Awash river basin to middle Abay River basin. This result is only if the groundwater flows according to the natural flow system, if there is an artificial withdrawal (like pumping) of the groundwater from either of the basins this result might change.
. The study faced both data quantity and quality problems. A further and detailed investigation has to be done to better understand the groundwater flow system of the area.
. The result of this study should be used to assess the potential for internal and cross contamination of the groundwater
Addis Ababa Institute of Technology | 53
6 References Abebayehu, A., Alemayehu, T., Endale, G., Sahle, T., Sileshi, D., & Belaynesh, B. (2015). Ethiopian panel on Climate Change . Addis Ababa: Ethiopian Academy of Sciences.
Alemayehu, T. (2006). Groundwater Occurance in Ethiopia. Addis Ababa: UNESCO.
Anderson, M. P., & Woessner, W. W. (1992). Applied Groundwater Modling: Simulation of flow and advective transport. California: Acadamic press.
Azagegn, T. (2015). Groundwater Dynamics in the Left Bank Catchments of the Middle Blue Nile and the Upper Awash River Basins, Central Ethiopia. Addis Ababa: Unpublished Ph.D Thesis.
Azagegne, T. (2008). Hydrogeochemical characterization of aquifer systems in Upper Awash River Basin and adjacent abay plateau using geochemical modeling and isotope hydrology. Addis Ababa: Unpublished.
Bear, J., & Cheng, A. H.-D. (2010). Modeling Groundwater Flow and Contaminant Transport. Newyork: Springer.
Belcher, W. R., Bedinger, M. S., Back, J. T., & Sweetkind, D. S. (2009). Interbasin flow in the Great Basin with special reference to the southern Funeral Mountains and the source of Furnace Creek springs, Death Valley, California, U.S. Journal of Hydrology, 30-43.
Belete, B., & Semu, A. (2013). Background report: Hydro-meteorological trends . Addis Ababa: AWASH RIVER BASIN WATER AUDIT (ARBWA) PROJECT.
Cook, P. G. (2003). A guide to regional groundwater flow in fractured rock aquifers. Australia : CSIRO Land and Water.
Energy, F. D. (2014, March 18). Federal Democratic Republic of Ethiopia Minisrty of Water & Energy. Retrieved December 21, 2016, from http://www.mowr.gov.et/index.php?pagenum=2.2
Fetter, C. (2001). Applied Hydrogeology. New Jersey: Merrill Publishing Company.
Gebreselassie, E. (2014, February 27). Ethiopia plans to tap groundwater as climate defence. Retrieved December 21, 2016, from Thomson Reuters Foundation News: http://news.trust.org//item/20140225161943-p7812/
Genereux, D. P., Wood, S. J., & Pringle, C. M. (2001). Chemical Tracing of interbasin groundwater transfer in the lowland rainforst os Costa Rica. Journal of Hydrology, 163- 178.
Hailu, K. (2016). Groundwater Dynamics in Tributary Streams of Muger. Addis Ababa: Unpublished.
Addis Ababa Institute of Technology | 54
Herbert, F., & Mary, P. (1982). Introduction to groundwater modeling: Finite difference and finite element methods. San Diego, California: Acadamic Press,Inc.
Kebede, S. (2013). Groundwater in Ethiopia. In S. Kebede, Chapter 7: Groundwater Potential, Recharge, Water balance: Vital Numbers (p. 221). Berlin: Springer Hydrogeology.
Mayo, S. T. (2014). The role of interbasin groundwater transfers in geologically complex terranes, demonstrated by the Great Basin in the western United States. Hydrogeology Journa.
Merz, S. K. (2013). Australian groundwater modelling guidelines: companion to the guidelines. Canberra : The National Water Commission .
Mohammed, M., & Ayalew, B. (2016). Modeling for Inter- Basin Groundwater Transfer Identification: The Case of Upper Rift Valley Lakes and Awash River Basins of Ethiopia. Journal of Water Resource and Protection, 1222- 1237.
Nelson, S., & L.Mayo, A. (2004). Testing the Interbasin Flow Hypothesis at Death Valley,California. Eos Transactions American Geophysical Union, 349,355-356.
Raymond, L. S. (1992). What is groundwater? New York: Cornell University pamphlet FO- 05867.
Todd, D. K., & Mays, L. W. (2005). Grondwater Hydrology. New Jersey: Jhon Wiley & Sons, Inc.
Uhegbu, ,. C., & Igboekwe, M. (2011). Fundamental Approach in Groundwater Flow and Solute Transport Modelling Using the Finite Difference Method. In I. A. Dar, Earth and Environmental Sciences. Nigeria: World's largest Science, Technology & Medicine Open Access book publisher.
USDA, U. D. (1967). Groundwater-Recharge. Technical Release No.36.
Vijai, S., & Rohit, G. (2011). Development of conceptual groundwater flow model for Pali Area, India. African Journal of Environmental Science and Technology Vol. 5(12), 1085-1092.
Warren, v., & Gary, L. (1996). Introduction to Hydrology . Mishawaka: Addison Wesley Longman.
WWDSE, W. W. (2008). Evaluation of water resources of Adaa and Becho plains groundwater resource for irrigation. Addis Ababa: Unpublished Report.
WWDSE, W. W. (2010). Addis Ababa Groundwater Development, And construction Supervision Project (40 deep wells). Addis Ababa: Unpublished Report.
Yitbarek, A. (2009). Hydrogeological and hydrochemical framework of complex volcanic system in the Upper Awash River basin, Central Ethiopia : with special emphasis on inter-basins groundwater transfer between Blue Nile and Awash rivers.
Addis Ababa Institute of Technology | 55
APPENDEX: well/spring data used in the numerical model Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 1 472772 1018752 2554 2 848 2 473693 1032100 2504 12.5 880 3 474556 983625 2162 39 219 4 475300 983800 2122 0 93 5 475300 984000 2115 0 129 6 474800 984700 2146 1 71 7 475650 984750 2119 57 0 8 476400 984800 2133 12 90 9 475050 985050 2124 5 24 10 474645 985501 2144 92 68 11 474648 985501 2144 86 117 12 474641 985622 2154 8 68 13 475000 985800 2164 0 120 14 476750 985800 2142 53 86 15 475000 987800 2164 28 172 16 482896 991871 2248 14 205 17 481230 992312 2262 22 200 18 475750 993650 2313 97 149 19 476963 994106 2341 73 132 20 476800 994200 2344 52 151 21 484821 994284 2324 42 368 22 477463 994346 2328 92 170 23 475600 994500 2323 41 139 24 483750 994550 2346 51 230 25 483453 994606 2337 1 182 26 476235 995275 2353 84 151 27 487300 995300 2364 88 120 28 478450 995600 2358 87 171 29 479450 995800 2353 32 0 30 478350 996700 2373.3 0 0 31 482770 997150 2387 35 137 32 477515 997474 2405 19 216
Addis Ababa Institute of Technology | 56
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 33 481650 997725 2416 43 145 34 476450 998100 2437 11 85 35 480395 998100 2440 9 0 36 476500 998250 2448 22 58 37 476100 998300 2435 17 54 38 480029 998401 2466 20 144 39 480431 998457 2455 15 181 40 480400 998500 2458 30 47 41 484190 998500 2492 45 140 42 476200 998600 2473 10 66 43 480629 998771 2487 14 96 44 475600 998900 2422 20 90 45 483350 999064 2501 59 116 46 475200 999200 2450 39 51 47 489127 999697 2441 39 280 48 482070 999823 2539 80 117 49 476105 1000050 2477 50 105 50 481878 1000148 2577 76 140 51 486000 1000707 2485 12 54 52 478850 1000950 2736.7 0 0 53 485925 1000975 2486 8 200 54 481337 1001017 2637 23 135 55 489200 1001025 2446 31 0 56 486200 1001042 2472 18 100 57 486000 1001115 2483 10 130 58 475000 1001300 2545 74 168 59 486712 1001378 2448 0 133 60 475800 1001500 2570 97 210 61 488243 1002102 2475 26 96 62 488161 1002129 2475 63 102 63 487800 1002200 2478 25 80 64 488150 1002300 2476 26 175 65 491300 1004800 2448 5 95 66 482263 1038145 2571 22 66 67 486182 1045145 2529.8 0 0
Addis Ababa Institute of Technology | 57
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 68 485000 1048933 2636.4 0 0 69 482960 1066600 2585.5 0 0 70 483180 1073086 2450.4 0 0 71 475697 979915 2060 10 448 72 472846 980785 2062 8 120 73 472836 980785 2062 8 481 74 472779 978788 2060 10 486 75 473597 981135 2073 22 500 76 474204 980459 2072 21 250 77 474918 980486 2077 22 480 78 471185 979580 2055 37 500 79 470469 979211 2054 15 506 80 472630 979912 2064 8 533 81 471909 979461 2060 9 501 82 473583 979260 2066 18 484 83 469612 978592 2056 23 514 84 472245 977865 2059 28 500 85 471476 977396 2056 34 480 86 471521 976630 2059 40 552 87 473944 978722 2070 30 492 88 473386 980122 2066 11 549 89 472460 981553 2067 0 500 90 471918 979657 2058 9 272 91 470557 976837 2056 54 269 92 471289 977837 2054 27 500 93 469835 978303 2054 53 540 94 468849 970179 2045 55 493 95 468353 972311 2054 62 480 96 468006 971498 2063 58 496 97 471909 978486 2058 108 480 98 489977 1000102 2344 10 500 99 438871 977186 2062 13 443 100 447224 978514 2061 13 440 101 449082 980399 2067 11 440 102 463973 991974 2341 45 405
Addis Ababa Institute of Technology | 58
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 103 463590 992116 2366 80 432 104 472912 1001627 2568 59 312 105 474203 1002351 2544 16 546 106 479316 999941 2642 118 271 107 479175 999755 2625 107 250 108 470682 987316 2218 0 357 109 466336 1000658 2519 97 420 110 465724 1002753 2602 85 332 111 470158 1001882 2611 62 506 112 470503 1002189 2637 99 410 113 480887 997740 2414 63 220 114 457823 1002833 2619 3 104 115 448290 1002698 2412 10 0 116 449177 1002158 2477 0 0 117 447200 998889 2295 0 126 118 446338 997431 2259 13 125 119 446632 994813 2242 1 80 120 453522 1001474 2568 58 115 121 457162 1001115 2625 7 115 122 459689 998340 2593 0 48 123 446266 1004147 2391 37 148 124 446155 1003073 2389 7 90 125 444997 1000718 2360 38 91 126 444626 1001034 2386 40 0 127 444168 998992 2294 7 98 128 445168 997226 2239 0 98 129 445942 1001323 2395 0 99 130 445773 1001323 2388 30 75 131 445099 1003816 2400 30 130 132 443050 1001649 2407 24 130 133 442635 1001366 2409 25 220 134 443132 1000869 2386 30 116 135 444677 998215 2288 6 100 136 444677 998808 2309 21 100 137 444642 1002960 2426 49 66
Addis Ababa Institute of Technology | 59
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 138 443984 999625 2311 10 70 139 444209 998733 2286 7 98 140 441584 1003445 2456 11 50 141 437892 1008952 2591 4 13 142 404656 997733 2232 22 81 143 427193 994953 2125 2 0 144 427164 996290 2157 0 37 145 434015 1000129 2341 5 147 146 440110 1001337 2422 37 153 147 465419 987294 2263 15 120 148 460810 981473 2229 67 102 149 460464 974637 2093 38 61 150 461930 970844 2204 144 183 151 462743 1002521 2626 35 250 152 463635 988675 2283 27 83 153 469672 993830 2324 17 167 154 455450 983014 2110 15 120 155 455426 982736 2105 16 150 156 453850 973096 2055 56 59 157 451420 971692 2066 58 60 158 444624 978143 2064 10 65 159 445354 969451 2092 39 71 160 445144 969045 2088 45 86 161 453538 982154 2088 8 80 162 442842 977555 2067 14 100 163 442811 977625 2065 10 179 164 447966 980422 2064 54 80 165 461412 986324 2277 45 145 166 459676 984947 2204 28 96 167 460937 986565 2277 46 114 168 463599 988583 2283 19 130 169 463742 985378 2363 18 125 170 427635 994816 2119 7 125 171 429252 993949 2110 15 45 172 436160 1000453 2360 37 153
Addis Ababa Institute of Technology | 60
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 173 435382 1000251 2356 10 206 174 466050 993650 2366 71 137 175 445180 1002459 2390 23 101 176 471400 988250 2208 6 88 177 432432 1024464 2607 11 161 178 474125 1001050 2565 28 154 179 466200 1001008 2540 23 53 180 467200 1001017 2536 35 152 181 473400 999600 2498 21 58 182 441366 977899 2062 8 10 183 441901 981393 2064 6 7 184 474200 997400 2427 0 200 185 441831 983807 2078 6 50 186 471300 998200 2453 17 88 187 469800 996300 2368 17 52 188 469900 996000 2350 14 67 189 469800 996200 2369 7 60 190 440595 1000333 2386 81 170 191 469725 994250 2328 17 142 192 472000 995100 2331 44 56 193 471300 995050 2326 0 114 194 469700 994500 2339 7 152 195 474395 995211 2352 59 153 196 468000 993200 2295 17 48 197 471200 993700 2305 23 85 198 473000 992700 2289 111 121 199 472900 992500 2280 90 156 200 474300 992700 2280 89 129 201 475600 994500 2323 41 139 202 473200 992400 2287 40 72 203 473100 991900 2285 113 154 204 473848 990072 2255 39 100 205 473600 988300 2192 11 102 206 473900 989000 2225 35 201 207 475000 987800 2164 28 172
Addis Ababa Institute of Technology | 61
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 208 475335 980717 2074 17 179 209 475300 983800 2122 0 93 210 473900 1001050 2566 15 200 211 475300 984000 2115 0 129 212 474300 1001005 2521 22 83 213 468400 1001016 2548 3 192 214 466600 1001003 2518 23 153 215 468300 1001003 2545 41 63 216 468800 1001007 2540 18 42 217 468900 1001007 2548 72 116 218 469900 1001000 2589 7 80 219 474000 999400 2475 7 50 220 473300 999300 2479 18 27 221 475600 998900 2422 20 90 222 463600 988200 2281 28 64 223 470000 996400 2353 14 44 224 470100 996100 2351 30 45 225 473400 996400 2354 0 200 226 473400 996300 2352 0 249 227 473100 996400 2348 0 249 228 473200 996300 2347 57 0 229 473200 996400 2347 0 100 230 473300 996100 2347 0 78 231 473300 996200 2348 8 56 232 473300 996300 2347 59 60 233 473400 995800 2347 6 50 234 472900 995900 2359 2 32 235 473000 996300 2348 2 80 236 472700 996300 2355 7 20 237 472500 996300 2361 9 41 238 471400 995900 2346 26 67 239 471600 995800 2352 19 34 240 471500 995900 2349 17 34 241 471400 995800 2344 12 64 242 471400 996000 2348 23 32
Addis Ababa Institute of Technology | 62
UTM Elevation SWL DEPTH No. UTM E N (m) (m) (m) 243 471500 996000 2350 19 46 244 471550 995950 2352 23 44 245 471500 995800 2348 16 52 246 471300 995800 2342 8 85 247 471800 995500 2345 8 62 248 471300 995400 2332 0 101 249 471300 994800 2315 4 62 250 470900 994800 2307 1 119 251 471700 995100 2326 7 62 252 471700 995000 2321 11 80 253 471700 994900 2316 10 56 254 469300 995500 2356 16 107 255 471700 986600 2259 26 81 256 471200 995700 2343 3 192 257 471300 996200 2353 6 47 258 471700 996300 2358 41 96 259 466300 993100 2336 60 112 260 466250 993050 2338 50 142 261 467200 993600 2331 48 84 262 468100 993100 2303 50 80 263 468100 993200 2299 45 83 264 471000 993800 2306 68 76 265 473334 997204 2371 4 355 266 472000 993500 2281 51 92 267 473100 992600 2289 36 84 268 473500 992900 2306 123 162 269 474300 993300 2319 126 214 270 473100 991800 2283 56 94 271 473100 991900 2285 113 154 272 473050 991800 2281 94 136 273 470465 991100 2223 16 124 274 470250 991500 2235 8 40 275 470300 991200 2229 10 20 276 470400 992100 2240 11 91 277 471400 991000 2248 26 38
Addis Ababa Institute of Technology | 63
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 278 473800 990250 2260 38 75 279 473750 990050 2253 52 146 280 473500 987900 2184 9 91 281 473230 988879 2210 14 68 282 473900 989000 2225 45 202 283 474000 989100 2226 18 58 284 474100 989000 2221 35 126 285 474050 996650 2382 10 400 286 473300 987700 2160 45 103 287 473300 987300 2157 35 120 288 468100 1016250 2579 3 193 289 475000 985800 2164 0 120 290 475662 980783 2071 27 52 291 465600 1001855 2555 56 83 292 476000 980900 2068 13 40 293 465243 1003393 2635 26 115 294 472400 998500 2458 5 43 295 472500 996600 2369 7 29 296 465507 1002282 2562 2 178 297 470950 995225 2319 0 115 298 472700 996500 2356 3 186 299 470500 994500 2326 42 170 300 466900 1001005 2537 20 150 301 471400 995900 2346 17 88 302 474225 982650 2155 31 178 303 474429 986829 2183 41 187 304 475300 983800 2122 0 140 305 455000 985200 2238 51 126 306 464300 990600 2292 14 52 307 473000 992700 2289 24 90 308 474050 1000875 2560 15 156 309 473326 986813 2157 25 87 310 462500 987000 2309 84 137 311 461900 974300 2127 38 0 312 459700 998075 2581 10 67
Addis Ababa Institute of Technology | 64
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 313 464000 997000 2510 51 100 314 463700 988500 2278 19 130 315 470800 982900 2109 0 114 316 473566 978610 2066 24 122 317 461500 1001023 2590 82 110 318 466200 988800 2249 0 100 319 466400 987600 2255 18 125 320 473069 979881 2061 6 116 321 473108 979851 2063 7 103 322 473350 1003000 2685 10 150 323 466175 1001800 2566 26 0 324 465900 1002875 2613 16 110 325 464600 1003075 2633 14 96 326 466440 1001760 2564 18 66 327 474075 989600 2236 24 60 328 473760 987300 2182 23 0 329 473925 987175 2182 16 72 330 455475 994995 2838 61 152 331 467150 992150 2280 29 94 332 455350 985100 2188 70 128 333 455300 985250 2198 38 101 334 455525 984000 2146 63 124 335 455550 983750 2138 47 181 336 444000 977700 2068 17 100 337 460850 985850 2251 43 106 338 460500 986500 2296 27 100 339 468650 995450 2342 26 126 340 468650 999800 2488 69 172 341 467100 1000550 2514 12 142 342 464500 1003150 2629 6 0 343 474500 995450 2346 66 201 344 468800 996600 2372 50 124 345 468200 1001600 2572 46 150 346 469050 994450 2329 27 120 347 468425 996350 2329 20 68
Addis Ababa Institute of Technology | 65
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 348 469280 993350 2303 20 122 349 468875 993750 2304 11 130 350 473900 993100 2313 118 201 351 470950 993300 2298 19 120 352 467250 999800 2513 59 70 353 474250 996800 2386 40 205 354 474175 996550 2377 40 120 355 472700 999800 2503 12 120 356 468100 1001625 2582 32 150 357 463850 993100 2403 84 150 358 470450 990125 2224 15 0 359 471400 988250 2208 13 84 360 472900 1003550 2710 4 0 361 465651 1001575 2545 7 76 362 467853 999379 2467 3 0 363 472150 993300 2278 51 150 364 463266 1001971 2604 53 111 365 465243 1003930 2689 26 115 366 470110 993850 2322 35 150 367 474957 982383 2147 24 135 368 466350 1001000 2541 16 153 369 469727 993542 2314 22 120 370 460121 985966 2254 40 120 371 470316 991064 2228 10 170 372 467000 996300 2364 52 132 373 463908 995127 2463 40 147 374 465410 1002944 2604 11 124 375 465161 1003103 2613 18 67 376 472541 996743 2371 52 90 377 464538 991302 2309 5 94 378 469804 993691 2322 27 170 379 474000 1001000 2570 40 201 380 457030 984617 2218 89 140 381 474788 982924 2159 24 124 382 473466 987247 2170 9 65
Addis Ababa Institute of Technology | 66
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 383 458646 984363 2190 44 161 384 470983 992553 2261 33 96 385 486000 1000707 2485 12 54 386 472975 1011144 2614 12 114 387 471799 999371 2478 8 114 388 472200 995700 2358 15 67 389 473209 996728 2355 0 300 390 472500 998700 2479 14 0 391 473900 985100 2171 8 72 392 463972 1000788 2517 0 174 393 464721 996788 2480 200 200 394 462260 984901 2284 83 180 395 471500 990500 2224 12 200 396 464031 1002909 2586 0 200 397 465578 999808 2471 0 193 398 467135 989840 2243 3 213 399 468261 990357 2240 4 213 400 470277 989578 2218 13 230 401 469245 990260 2232 0 240 402 465741 989188 2254 3 134 403 468512 989680 2230 0 130 404 469458 990594 2233 0 181 405 468196 990422 2241 5 180 406 467723 990028 2236 4 161 407 470790 990330 2219 0 240 408 465591 989872 2267 8 257 409 465295 990132 2273 10 200 410 463985 991540 2323 25 185 411 466600 1001250 2532 7 196 412 471125 989636 2211 11 153 413 470070 991000 2233 10 170 414 469500 989600 2224 4 150 415 463800 994650 2460 41 147 416 463595 995915 2486 66 158 417 466308 989421 2249 4 185
Addis Ababa Institute of Technology | 67
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 418 469322 1001428 2571 0 240 419 468196 998300 2425 26 200 420 470530 991988 2235 35 170 421 460295 986769 2314 31 158 422 447549 1007893 2509 24 203 423 421795 1040108 2447 20 146 424 474421 1013070 2608 18 304 425 450359 981037 2076 11 280 426 440274 1006055 2530 12 300 427 427395 992768 2101 6 220 428 455620 1026514 2603 8 273 429 473911 1031930 2519 1 324 430 431584 998853 2319.1 0 0 431 410870 997013 2191.4 0 0 432 459831 985582 2226.5 0 0 433 455287 985619 2234.4 0 0 434 468338 1076180 2735.5 0 0 435 464032 1073742 2804.7 0 0 436 466350 1074642 2764.9 0 0 437 469877 1077013 2737.2 0 0 438 455664 1027096 2597 0 0 439 451249 985378 2153.3 0 0 440 460950 976800 2110.1 0 0 441 466600 1001990 2572.6 0 0 442 463259 1002487 2605.3 0 0 443 469300 966775 1953.5 0 0 444 468500 967750 1967.4 0 0 445 468750 967100 1963.2 0 0 446 450887 981258 2079 12.17 436 447 451632 979475 2070 7.18 482 448 450187 981027 2074 8.7 440 449 423439 988990 2074 0 450 450 430759 1035489 2486 0 0 451 430128 1037894 2482 0 0 452 430592 1037170 2492 0 0
Addis Ababa Institute of Technology | 68
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 453 474424 1001212 2491 40 260 454 475068 1001254 2525 105 258 455 475945 1000580 2478 44 252 456 475638 999991 2444 23 0 457 474238 1002373 2544 68 0 458 470504 1002135 2629 0 232 459 470218 1001886 2602 0 233 460 472608 1002066 2572 0 0 461 471026 1002023 2631 23 222 462 466842 993128 2294 38 250 463 482682 994124 2282 38 0 464 481681 994296 2280 12 260 465 482349 995063 2310 52 210 466 482109 993423 2277 37 228 467 484883 994701 2313 16 250 468 485228 994341 2301 12.4 250 469 485664 994125 2291 1 250 470 481462 998906 2452 72 200 471 480321 997370 2374 10 0 472 482994 998429 2422 44 203 473 482849 991509 2224 7 270 474 480604 992935 2250 0 260 475 481101 991646 2228 25 250 476 481061 992052 2232 28 270 477 480760 992453 2252 22 260 478 467660 996912 2349 12 270 479 468268 996584 2324 5 250 480 468505 995156 2284 0 250 481 487881 997599 2366 0 200 482 486723 1000881 2410 17 250 483 464527 990017 2264 13 228 484 468110 1001421 2562 66 250 485 470994 987635 2206 58 0 486 466130 994219 2371 85 250 487 468148 989664 2216 1.3 182
Addis Ababa Institute of Technology | 69
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 488 477550 997650 2394 18.86 216 489 469150 1001150 2541 0 240 490 480999 999648 2496 12 228 491 481519 999648 2491 5 200 492 473400 999600 2471 21 57.9 493 473100 992600 2259 36 84 494 473900 989000 2206 45.4 201.5 495 468100 993200 2287 45 83 496 471200 993700 2279 23.3 85 497 471300 998200 2437 16.5 87.5 498 469800 996300 2356 16.5 51.9 499 469900 996000 2334 13.7 67.1 500 471500 995900 2333 17 34 501 471400 995800 2321 12 64 502 471400 996000 2330 23 32.4 503 471500 996000 2334 19.4 46 504 471500 995800 2326 16 52 505 471300 995800 2321 7.6 85 506 471400 995900 2328 16.8 88 507 473100 991900 2263 112.7 153.9 508 473100 991800 2265 56.4 93.9 509 473100 991900 2263 112.7 153.9 510 471300 994800 2287 4.1 62 511 469800 996200 2344 7 60 512 471300 995050 2312 0 114 513 471300 995400 2309 0 100.5 514 468800 1001007 2514 18 42 515 473300 987700 2145 44.7 103 516 473100 996400 2331 0 249 517 471700 994900 2301 10.4 55.5 518 474300 1001005 2514 22 83 519 473000 996300 2333 1.83 80 520 472000 995100 2303 44 56.4 521 473300 996200 2330 7.6 56.4 522 473300 996100 2333 0 77.7
Addis Ababa Institute of Technology | 70
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 523 473300 996300 2330 59 60 524 467200 1001017 2516 35.3 150 525 471400 991000 2216 25.9 38.1 526 471400 988250 2187 5.93 88 527 471700 986600 2243 26.1 81 528 474050 996650 2352 9.8 400 529 468196 990422 2223 4.8 180 530 465243 1003393 2606 26.17 115 531 475300 984000 2106 0 128.5 532 474928 982697 2152 0 104 533 471500 990500 2200 12.28 200 534 466600 1001250 2508 7.26 196 535 465243 1003930 2654 26.17 115 536 466350 1001000 2512 15.65 153 537 470888 987426 2202 0 114 538 466600 1001003 2508 22.6 153 539 475000 1001300 2523 73.54 168 540 468100 1001625 2559 31.69 150 541 470950 995225 2305 0 115 542 470900 995075 2288 0 121.5 543 473300 987300 2145 35.39 120 544 473300 999300 2451 18 27 545 476078 1000763 2490 0 252 546 468482 1030170 2533 45 300 547 473008 1010984 2610 0 123 548 433779 1000228 2336 1.1 193.2 549 430267 987498 2058 0 0 550 487089 997218 2382 0 0 551 484379 1066656 2565 0 0 552 466430 994219 2338 0 250 553 445643 973409 2122 0 0 554 466662 970715 2050 0 0 555 464607 973547 2134 0 0 556 466690 976790 2061 0 0 557 378351 991473 2177 22.5 147
Addis Ababa Institute of Technology | 71
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 558 378444 991683 2169 89.48 143 559 378447 991365 2176 32.89 130 560 474740 1028068 2606 0 0 561 482111 1056765 2628 0 0 562 464612 1034331 2443 19 150 563 391948 993451 2402 0 0 564 489669 996423 2350 0 0 565 487268 995400 2350 0 280 566 465017 995123 2414 37.58 250 567 480506 1057527 2649 0 0 568 435083 1016838 2570 0 0 569 477181 1065914 2630 3 21 570 471304 1027754 2540 3 65 571 420468 995608 2153 5 21 572 487920 1003552 2458 0 0 573 502053 1042307 2635 0 0 574 478667 1066530 2610 6 150 575 478884 1037765 2570 8 150 576 456092 1047297 1500 20 150 577 488219 1067941 2636 2 12 578 481165 992219 2235 27.59 270 579 481213 991853 2232 25.52 250 580 480717 993193 2257 0 260 581 480863 992647 2241 0 260 582 485841 1067849 2605 6 8 583 432500 1024270 2585 2.1 182 584 484874 1061850 2614 0 0 585 485003 1061595 2614 0 0 586 470851 1027852 2473 0 157 587 440140 1000993 2380 0 0 588 475165 1001449 2522 106.4 260 589 448223 1081244 2853 6 60 590 406722 1009647 3005 6 150 591 486042 1061037 2621 1 10 592 484876 1060344 2651 4.32 4.75
Addis Ababa Institute of Technology | 72
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 593 486122 1061084 2621 0.44 0 594 485112 1060794 2643 0 13 595 485646 1061481 2627 0 13.5 596 489927 1000153 2348 9.69 500 597 401157 996412 2305 24.5 302 598 401801 996640 2313 31.2 246 599 401587 997298 2301 21.52 302 600 400975 997008 2290 19 302 601 490754 1056754 2671 4 6 602 480850 1065676 2626 5 15 603 459862 1086322 3010 32.94 141 604 465729 1002755 2575 52.4 270 605 468094 1001478 2561 66.25 250 606 482884 1061461 2622 2 0 607 440303 1006061 2514 0 300 608 444577 998364 2273 0 140 609 444677 998215 2273 5.9 100 610 448532 1008047 2502 0 0 611 428348 1027771 2507 0 0 612 479631 995410 2329 0 0 613 474463 1022973 2571 5 50 614 485982 1052616 2634 2 150 615 487685 1060862 2643 0 13 616 487590 1060127 2635 2.4 5 617 487021 1060473 2627 3 4.2 618 377136 1058057 2052 41 123 619 476660 1066674 2639 0 0 620 493757 1054356 2656 0 0 621 482000 1059755 2622 2 16 622 427131 996390 2135 0 50 623 474590 1068254 2641 6 43.4 624 471985 987830 2194 0 0 625 461197 1084145 3030 2 50 626 469191 989547 2213 4.15 230 627 486738 1001391 2435 8.14 250
Addis Ababa Institute of Technology | 73
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 628 493003 1051307 2639 25.4 492 629 493215 1051415 2636 5.7 90 630 494345 1051950 2647 25.4 492 631 492919 1054913 2663 5 15 632 489334 1058282 2650 5 50 633 473800 1024726 2608 0 0 634 386800 992200 2367 0 0 635 478950 1072305 2584 10 25 636 466601 1001250 2508 0 133 637 485290 994522 2302 12.42 253 638 473900 985100 2144 8 72 639 472700 996500 2358 2.6 186 640 472500 996600 2353 7 29 641 472900 992500 2264 89.6 156.2 642 473500 992900 2283 123.3 162 643 475578 1035082 2604 0 0 644 433672 1023691 2580 45.9 602 645 424332 1036895 2455 0 216 646 380457 991815 2197 0 147 647 486257 1054859 2639 7 10 648 486419 1054881 2639 0 0 649 485504 1056537 2618 0 0 650 485511 1056545 2618 14 181 651 473400 996400 2334 0 200 652 473400 996300 2330 0 0 653 475000 987800 2147 27.8 172 654 468800 996600 2336 50.35 124 655 481368 997713 2396 88.37 260 656 472700 999800 2463 11.7 120 657 469300 995500 2329 16 107 658 474300 1001014 2514 0 108 659 472500 996300 2368 8.7 41 660 464387 1034248 2451 20 180 661 471700 995100 2306 7.4 62 662 474000 989100 2198 18 58
Addis Ababa Institute of Technology | 74
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 663 471700 995000 2306 10.8 80 664 453986 1025102 2602 3 250 665 484862 1057540 2618 6.4 8.4 666 483172 1061127 2623 28.15 180 667 484835 1054492 2641 0 0 668 474238 1002370 2544 67.94 184 669 472000 993500 2256 50.5 92 670 483377 1061889 2633 1.7 13 671 473400 995800 2327 6 50 672 469900 1001000 2554 7 80 673 472900 995900 2347 1.5 32 674 438871 977181 2051 12.65 443 675 468100 1016250 2570 3 193 676 482163 993603 2269 36.35 250 677 484971 994879 2311 15.64 290 678 485733 994302 2291 74 210 679 432020 1025151 2599 2.5 180 680 472826 980785 2045 8.18 121.5 681 472600 997500 2363 0 96 682 459800 998250 2566 0 68.5 683 471400 995900 2328 26.1 88 684 448502 978502 2051 12.56 440 685 474300 993300 2298 126 214 686 466200 1001008 2510 22.6 53 687 468227 1081132 2932 15 110 688 472700 996300 2345 6.8 20 689 474000 999400 2455 6.8 50 690 467200 993600 2319 48 84 691 483800 1065398 2587 1.5 15 692 483052 1065400 2600 1 2 693 447488 1004519 2401 0 0 694 475154 1018844 2573 2 68 695 473038 1008484 2649 4.2 460 696 473595 981135 2072 11 500 697 474918 980496 2063 21.8 392
Addis Ababa Institute of Technology | 75
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 698 471909 979461 2044 8.8 500.8 699 415726 995659 2156 0 0 700 466306 1008828 2653 4.2 460 701 469142 966835 1922 0 0 702 450215 1089393 2804 0 0 703 448316 1080574 2844 0 0 704 497025 1066349 2577 0 0 705 448147 1080415 2825 0 0 706 459891 1085626 3032 0 0 707 453668 998788 2575 0 0 708 464923 992809 2322 0 0 709 475208 1003085 2622 0 0 710 469414 1001640 2557 0 0 711 457026 981375 2065 0 0 712 472633 983922 2117 0 0 713 451196 1027438 2673 0 0 714 473890 1087756 1912 0 0 715 457146 1004953 2649 0 0 716 449761 1074642 2693 0 0 717 463999 1018139 2616 0 0 718 491646 1015075 2620 0 0 719 482298 1076328 2009 0 0 720 482754 1073368 2413 0 0 721 482345 1066564 2600 0 0 722 482195 1076192 2136 0 0 723 466350 1074642 2771 0 0 724 441075 1108904 1662 0 0 725 480642 1069101 2644 0 0 726 486175 1045151 2513 0 0 727 470338 1035426 2558 0 0 728 486762 1062813 2606 0 0 729 454124 1002590 2604 0 0 730 438835 1085623 2543 0 0 731 494307 1049796 2632 0 0 732 443366 1111042 1125 0 0
Addis Ababa Institute of Technology | 76
Elevation SWL DEPTH No. UTM E UTM N (m) (m) (m) 733 447470 1064576 1951 0 0 734 413501 1037036 2585 0 0 735 468163 1081306 2926 0 0 736 447624 1078948 2742 0 0 737 459951 1048382 1745 0 0 738 457250 1095777 2158 0 0 739 464186 1065719 2558 0 0 740 473823 1088329 1822 0 0 741 475032 1087994 1965 0 0 742 426391 1042935 2517 0 0 743 470776 1007219 2671 0 0 744 483313 1005608 2596 0 0 745 492323 1060902 2665 0 0 746 451615 1027364 2662 0 0 747 484180 1059881 2627 0 0 748 484181 1059882 2627 0 0 749 447123 1093293 2433 0 0 750 385386 1052257 1906 0 0 751 472110 1009390 2677 0 0 752 380547 990709 2245 0 0 753 472859 1009905 2647 0 0 754 491203 1004462 2437 0 0 755 441088 1013105 2700 0 0 756 386845 1043913 1776 0 0 757 465410 1075177 2829 0 0 758 478357 1075318 2565 0 0 759 492039 1005044 2452 0 0 760 466264 996974 2393 0 0
Addis Ababa Institute of Technology | 77